In this paper, we study a secure integrated sensing and communication (ISAC) system employing a full-duplex base station with sensing capabilities against a mobile proactive adversarial target—a malicious unmanned aerial vehicle (M-UAV). We develop a game-theoretic model to enhance communication security, radar sensing accuracy, and power efficiency. The interaction between the legitimate network and the mobile adversary is formulated as a non-cooperative Stackelberg game (NSG), where the M-UAV acts as the leader and strategically adjusts its trajectory to improve its eavesdropping ability while conserving power and avoiding obstacles. In response, the legitimate network, acting as the follower, dynamically allocates resources to minimize network power usage while ensuring required secrecy rates and sensing performance. To address this challenging problem, we propose a low-complexity successive convex approximation (SCA) method for network resource optimization combined with a deep reinforcement learning (DRL) algorithm for adaptive M-UAV trajectory planning through sequential interactions and learning. Simulation results demonstrate the efficacy of the proposed method in addressing security challenges of dynamic ISAC systems in 6G, i.e., achieving a Stackelberg equilibrium with robust performance while mitigating the adversary’s ability to intercept network signals.

The approximate message passing (AMP)-based data detection is a highly effective solution for terahertz (THz) multiple-input multiple-output (MIMO) communications, enabling reliable data detection at ultra-high data rates. However, in the uplink of THz MIMO systems, high channel correlation leads to performance degradation and computational inefficiencies. To address these challenges, we develop correlated probability estimation (CPE) for the standard AMP iterative data detection algorithm (AMP-IDA), achieving Bayesian-optimal (BO) bit error rate (BER) performance in highly correlated THz channels. To mitigate the significant computational complexity of CPE, we propose an effective signal-to-noise ratio (eSNR)-adjusted channel decorrelation preprocessing (ACDP) method, which leverages whitening transformation and convex optimization, mitigating the impact of row correlation without prior knowledge of correlation indices. By integrating eSNR-ACDP with the low-complexity standard AMP-IDA, we design the ACDP-AMP-IDA, which attains BER close to the BO benchmark with significantly reduced complexity. Compared to orthogonal AMP (OAMP) algorithms, ACDP-AMP-IDA outperforms standard OAMP by up to 8 dB and achieves performance comparable to OAMP with linear minimum mean square error (MMSE) while incurring only 3%–6% of its runtime. Additionally, it surpasses existing AMP-IDA-based and MMSE detectors by over 10 dB and guarantees robust convergence across various transmitter-receiver distances in uplink THz MIMO systems.

This work studies near-field secure communications through transmit beamfocusing. We examine the benefit of having a protected eavesdropper-free zone around the legitimate receiver, and we determine the worst-case secrecy performance against a potential eavesdropper located anywhere outside the protected zone. A max-min optimization problem is formulated for the beamfocusing design with and without artificial noise transmission. Despite the NP-hardness of the problem, we develop a synchronous gradient descent-ascent framework that approximates the global maximin solution. A low-complexity solution is also derived that delivers excellent performance over a wide range of operating conditions. We further extend this study to a scenario where it is not possible to physically enforce a protected zone. To this end, we consider secure communications through the creation of a virtual protected zone using a full-duplex legitimate receiver. Numerical results demonstrate that exploiting either the physical or virtual receiver-centered protected zone with appropriately designed beamfocusing is an effective strategy for achieving secure near-field communications.

We propose a novel framework to analyze the coverage performance of three-dimensional (3D) indoor terahertz (THz) communication systems and examine the impact of the location of a user equipment (UE) on such performance. Specifically, we employ Manhattan line processes to precisely characterize the deployment of wall blockages in the indoor environment. Moreover, we model locations of access points (APs) using a Poisson point process and adopt the nearest line-of-sight AP association strategy. Due to the high penetration loss caused by wall blockages, we consider that a UE, its associated AP, and interfering APs are all in the same rectangular area, i.e., a room. Based on the proposed rectangular area model, we first analyze the impact of the location of a UE on the distance to its associated AP. We then derive a new expression for the coverage probability by adopting the fluctuating two-ray distribution to accurately model the small-scale fading in THz communications. Supported by simulation results, we validate our analysis and demonstrate how the location of the UE affects its coverage probability, offering valuable insights for meeting the coverage requirements of future THz communication system deployments.

In this paper, we develop a tractable analytical framework for a three-dimensional (3D) indoor terahertz (THz) communication system to theoretically assess the impact of the pointing error on its coverage performance. Specifically, we model the locations of access points (APs) using a Poisson point process, human blockages as random cylinder processes, and wall blockages through a Boolean straight line process. A pointing error refers to beamforming gain and direction mismatch between the transmitter and receiver. We characterize it based on the inaccuracy of location estimate. We then analyze the impact of this pointing error on the received signal power and derive a tractable expression for the coverage probability, incorporating the multi-cluster fluctuating two-ray distribution to accurately model small-scale fading in THz communications. Aided by simulation results, we corroborate our analysis and demonstrate that the pointing error has a pronounced impact on the coverage probability. Specifically, we find that merely increasing the antenna array size is insufficient to improve the coverage probability and mitigate the detrimental impact of the pointing error, highlighting the necessity of advanced estimation techniques in THz communication systems.

This work studies near-field secure communications empowered by beamfocusing and demonstrates, for the first time, the benefit of having a protected eavesdropper-free zone around the legitimate receiver. We consider the worst-case secrecy performance against an eavesdropper potentially located anywhere outside the protected zone. Under this consideration, a max-min optimization problem for beamfocusing design is formulated, which can be interpreted as a two-player sequential game between the transmitter and eavesdropper. Despite the NPhardness of the problem, we propose a synchronous gradient descent ascent framework that approximates the global maximin solution. Moreover, we present a low-complexity heuristic beamfocusing solution that delivers excellent performance over a wide range of scenarios. Numerical results demonstrate that exploiting the receiver-centered protected zone with appropriately designed beamfocusing is an effective strategy for achieving near-field secure communications.

Backscatter communication and harvest-then-transmit (HTT) communication are regarded as promising technologies for enabling green Internet of Things (IoT). The current works on the joint use of backscatter communication and HTT are limited in single cell scenarios with the fixed backscatter-then-HTT transmission structure. In this work, we propose a transmission scheme with flexible mode selection for the hybrid backscatter-HTT multi-cell system to achieve much improved communication performance, and then study the joint design for such a system. Specifically, by utilizing multi-antenna technology and enabling the flexible mode selecting between backscatter and HTT, a novel transmission scheme is developed. With the aim to maximize the sum rate of the considered system, we formulate a joint optimization problem for the base station transmission beamforming (TB), the transmission mode (TM), and the transmit power (TP) of the hybrid backscatter-HTT devices. To address the formulated non-convex problem, we propose a block coordinate descent-based algorithm, namely J3TO, to jointly optimize TB, TM, and TP, by decoupling the original problem into three sub-problems. Therein, the weighted minimum mean square error approach, matching theory, and the fractional programming technique are leveraged to deal with the sub-problems efficiently. Simulation results show that the proposed algorithm flexibly integrates the merits of backscatter and HTT technologies, achieving superior performance across various scenarios, compared with the benchmark schemes, e.g., backscatter-only SDMA, HTT-only SDMA, and backscatter-HTT TDMA.

In this work, we propose an adaptive system design for an Internet of Things (IoT) monitoring network with latency and reliability requirements, where IoT devices generate time-critical and event-triggered bursty traffic, and an unmanned aerial vehicle (UAV) aggregates and relays sensed data to the base station. Existing transmission schemes based on the overall average traffic rates over-utilize network resources when traffic is smooth, and suffer from packet collisions when traffic is bursty which occurs in an event of interest. We address such problems by designing an adaptive transmission scheme employing multiuser shared access (MUSA) based grant-free non-orthogonal multiple access and use short packet communication for low latency of the IoT-to-UAV communication. Specifically, to accommodate bursty traffic, we design an analytical framework and formulate an optimization problem to maximize the performance by determining the optimal number of transmission time slots, subject to the stringent reliability and latency constraints. We compare the performance of the proposed scheme with a non-adaptive power-diversity based scheme with a fixed number of time slots. Our results show that the proposed scheme has superior reliability and stability in comparison to the state-of-the-art scheme at moderate to high average traffic rates, while satisfying the stringent latency requirements.

In this paper, we investigate the secure transmission design for simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-assisted multiple-input multiple-output (MIMO) systems. By considering both perfect and imperfect channel state information (CSI) scenarios, we jointly optimize the covariance matrix of the transmitter and the transmitting and reflecting coefficients of the STAR-RIS and formulate two transmit power minimization problems. For the optimization problem in the perfect CSI scenario, we develop a penalty-based alternating optimization (AO) algorithm to handle it. For the optimization problem in the imperfect CSI scenario, this paper is the first work to study the robust beamforming design for STAR-RIS-assisted secure MIMO systems. To address this challenging problem, we first use the inequalities of the determinant to transform it into an equivalent form. Then, we use the generalized S-procedure to handle the worst-case constraints. Finally, we develop a penalty-based AO algorithm. Performance evaluation results show that the two proposed optimization algorithms significantly reduce the transmit power compared to other baseline schemes.

In this paper, we develop a novel analytical framework for a three-dimensional (3D) indoor terahertz (THz) communication system. Our proposed model incorporates more accurate modeling of wall blockages via Manhattan line processes and precise modeling of THz fading channels via a multi-cluster fluctuating two-ray (MFTR) channel model. We also account for traditional unique features of THz, such as molecular absorption loss, user blockages, and 3D directional antenna beams. Moreover, we model locations of access points (APs) using a Poisson point process and adopt the nearest line-of-sight AP association strategy. Due to the high penetration loss caused by wall blockages, we consider that a user equipment (UE) and its associated AP and interfering APs are all in the same rectangular area, i.e., a room. Based on the proposed rectangular area model, we evaluate the impact of the UE’s location on the distance to its associated AP. We then develop a tractable method to derive a new expression for the coverage probability by examining the interference from interfering APs and considering the MFTR fading experienced by THz communications. Aided by simulation results, we validate our analysis and demonstrate that the UE’s location has a pronounced impact on its coverage probability. Additionally, we find that the optimal AP density is determined by both the UE’s location and the room size, which provides valuable insights for meeting the coverage requirements of future THz communication system deployment.

The beam split effect (BSE) can result in a serious loss in achievable rate in terahertz (THz) transmission. In this work, we propose a new sub-band assignment scheme in a multiuser THz communications system to address the BSE. We consider a base station employs true-time-delay hardware between radio frequency chains and uniform planar arrays (UPAs). The core idea of this hardware is that, rather than fine-tuning the UPA delays to form a single beam from each UPA, we facilitate multi-beam transmission from each UPA. We derive a novel expression for the maximum sub-band bandwidth for UPA, ensuring that the BSE is avoided within each beam. Based on this expression we design sub-band assignment across users and power allocation among sub-bands to maximize the sum-rate, relying on the principles of beam multiplexing and aggregation (BMA). Using numerical results, we demonstrate (i) the merits of our proposed sub-band assignment in contrast to the distance-aware sub-band assignment scheme, (ii) the effectiveness of BMA in comparison with the BSE, and (iii) the improved performance resulting from our proposed optimal power allocation relative to equal power allocation.

This paper presents a secrecy performance study of a wiretap communication system with finite blocklength (FBL) transmissions over Rayleigh fading channels, based on the definition of an average information leakage (AIL) metric. We evaluate the exact and closed-form approximate AIL performance, assuming that only statistical channel state information (CSI) of the eavesdropping link is available. Then, we reveal an inherent statistical relationship between the AIL metric in the FBL regime and the commonly-used secrecy outage probability in conventional infinite blocklength communications. Aiming to improve the secure communication performance of the considered system, we formulate a blocklength optimization problem and solve it via a low-complexity approach. Next, we present numerical results to verify our analytical findings and provide various important insights into the impacts of system parameters on the AIL. Specifically, our results indicate that i) compromising a small amount of AIL can lead to significant reliability improvements, and ii) the AIL experiences a secrecy floor in the high signal-to-noise ratio regime.

This paper proposes a transmit power adaptation design for goal-oriented communication to improve the goal-acquisition performance over fading channels. The specific contribution lies in the power adaptation module which is capable of determining an appropriate transmit power based on the instantaneous channel condition, while satisfying an average power constraint. Moreover, it is a standalone add-on module that can be used in conjunction with different encoders. To illustrate its performance, we consider an image classification task as an example of goal acquisition and adopt the deep-learning-based joint source-channel coding for transmitting the goal-related information. We numerically illustrate the difference between the power adaptation design for goal-oriented communication and the traditional power adaptation design for bit-oriented communication. Our results demonstrate the performance gain from using the proposed power adaptation design and provide insights into conditions under which such a performance gain becomes either negligible or notable.

The temporary events are generally gathered around many users interested in the same content. An unmanned aerial vehicle (UAV) with caching and multicasting is attractive for such scenarios with high traffic demands, since the multicasting allows concurrently serving users, and the caching can alleviate the burden on backhaul links. Hence, in this work, we investigate a cellular network assisted by caching-and-multicasting-empowered UAVs, where UAVs multicast the files from their caching storage or base stations via wireless backhaul links. Particularly, a popularity-aware (PA) file selection and multicast scheme is proposed, where the files to be multicasted are determined by the instantaneous requested popularity, the maximum number of allowable fetched files and the performance on wireless backhaul links. By leveraging stochastic geometry, we obtain the approximated yet accurate result for the average number of successfully multicasted users. Our results confirm the effectiveness of the PA scheme, i.e., achieving a larger average number of successfully multicasted users compared to the random scheme for most cases. Moreover, the results suggest that a relatively smaller number of multicast channels or reducing the maximum number of allowable fetched files can benefit network performance in the case of the high signal-to-interference ratio threshold on the backhaul links.

Recently proposed splitting receivers, utilizing both coherently and non-coherently processed signals for detection, have demonstrated remarkable performance gain compared to conventional receivers in the single-antenna scenario. In this paper, focusing on a single-input multiple-output (SIMO) setup, we propose a multi-antenna splitting receiver, where the received signal at each antenna is split into an envelope detection (ED) branch and a coherent detection (CD) branch, and the processed signals from both branches of all antennas are then jointly utilized for recovering the transmitted information. We derive a closed-form approximation of the achievable mutual information (MI), in terms of the key receiver design parameters including the power splitting ratio at each antenna and the signal combining coefficients from all the ED and CD branches. We further optimize these receiver design parameters and demonstrate important design insights for the proposed multi-antenna ED-CD splitting receiver: 1) the optimal splitting ratio is identical at each antenna, and 2) the optimal combining coefficients for the ED and CD branches are the same, and each coefficient is proportional to the corresponding antenna’s channel power gain. Our numerical results also demonstrate the MI performance improvement of the proposed receiver over conventional non-splitting receivers.

This paper studies an extremely large-scale reconfigurable intelligent surface (XL-RIS) empowered covert communication system in the near-field region. Alice covertly transmits messages to Bob with the assistance of the XL-RIS, while evading detection by Willie. To enhance the covert communication performance, we maximize the achievable covert rate by jointly optimizing the hybrid analog and digital beamformers at Alice, as well as the reflection coefficient matrix at the XL-RIS. An alternating optimization algorithm is proposed to solve the joint beamforming design problem. For the hybrid beamformer design, a semi-closed-form solution for fully digital beamformer is first obtained by a weighted minimum mean-square error based algorithm, then the baseband digital and analog beamformers at Alice are designed by approximating the fully digital beamformer via manifold optimization. For the XL-RIS’s reflection coefficient matrix design, a low-complexity alternating direction method of multipliers based algorithm is proposed to address the challenge of large-scale variables and unit-modulus constraints. Numerical results unveil that i) the near-field communications can achieve a higher covert rate than the far-field covert communications in general, and still realize covert transmission even if Willie is located at the same direction as Bob and closer to the XL-RIS; ii) the proposed algorithm can enhance the covert rate significantly compared to the benchmark schemes; iii) the proposed algorithm leads to a beam diffraction pattern that can bypass Willie and achieve high-rate covert transmission to Bob.

Short-packet communication (SPC) and unmanned aerial vehicles (UAVs) are anticipated to play crucial roles in the development of 5G-and-beyond wireless networks and the Internet of Things (IoT). In this paper, we propose a secure SPC system, where a UAV serves as a mobile decode-and-forward (DF) relay, periodically receiving and relaying small data packets from a remote IoT device to its receiver in two hops with strict latency requirements, in the presence of an eavesdropper. This system requires careful optimization of important design parameters, such as the coding blocklengths of both hops, transmit powers, and the UAV’s trajectory. While the overall optimization problem is nonconvex, we tackle it by applying a block successive convex approximation (BSCA) approach to divide the original problem into three subproblems and solve them separately. Then, an overall iterative algorithm is proposed to obtain the final design with guaranteed convergence. Our proposed low-complexity algorithm incorporates robust trajectory design and resource management to optimize the effective average secrecy throughput of the communication system over the course of the UAV-relay’s mission. Simulation results demonstrate significant performance improvements compared to various benchmark schemes and provide useful design insights on the coding blocklengths and transmit powers along the trajectory of the UAV.

Physical-layer security (PLS) is a promising technique to complement more traditional means of communication security in beyond-5G wireless networks. However, studies of PLS are often based on ideal assumptions such as infinite coding blocklengths or perfect knowledge of the wiretap link’s channel state information (CSI). In this work, we study the performance of finite blocklength (FBL) transmissions using a new secrecy metric — the average information leakage (AIL). We evaluate the exact and approximate AIL with Gaussian signaling and arbitrary fading channels, assuming that the eavesdropper’s instantaneous CSI is unknown. We then conduct case studies that use artificial noise (AN) beamforming to analyze the AIL in both Rayleigh and Rician fading channels. The accuracy of the analytical expressions is verified through extensive simulations, and various insights regarding the impact of key system parameters on the AIL are obtained. Particularly, our results reveal that allowing a small level of AIL can potentially lead to significant reliability enhancements. To improve the system performance, we formulate and solve an average secrecy throughput (AST) optimization problem via both non-adaptive and adaptive design strategies. Our findings highlight the significance of blocklength design and AN power allocation, as well as the impact of their trade-off on the AST.

In this paper, we propose a secure short-packet communication (SPC) system involving an unmanned aerial vehicle (UAV)-aided relay in the presence of a terrestrial passive eavesdropper. The considered system, which is applicable to various next-generation Internet-of-Things (IoT) networks, exploits a UAV as a mobile relay, facilitating the reliable and secure exchange of intermittent short packets between a pair of remote IoT devices with strict latency. Our objective is to improve the overall secrecy throughput performance of the system by carefully designing key parameters such as the coding blocklengths and the UAV trajectory. However, this inherently poses a challenging optimization problem that is difficult to solve optimally. To address the issue, we propose a low-complexity algorithm inspired by the block successive convex approximation approach, where we divide the original problem into two subproblems and solve them alternately until convergence. Numerical results demonstrate that the proposed design achieves significant performance improvements relative to other benchmarks, and offer valuable insights into determining appropriate coding blocklengths and UAV trajectory.

We study the age of information (AoI) performance of a multiuser downlink system where a base station generates and transmits status updates to multiple user equipments (UEs). The question of whether to adopt broadcast transmission or distributed transmission for the optimal AoI performance is addressed analytically. In the broadcast transmission scheme, the status update for all UEs is jointly encoded into a packet for transmission, while in the distributed transmission scheme, the status update for each UE is encoded individually and transmitted by following the round robin policy. We first derive new closed-form expressions for the average AoI achieved by two transmission schemes. Then, we provide a criterion for selecting the better transmission scheme for a remote control system. Aided by simulation results, we investigate the impact of system parameters on the average AoI. For example, the distributed transmission scheme is more appropriate for the system with a large number UEs; otherwise, the broadcast transmission scheme is more appropriate.

In this paper, we analyze the non-linear age of information (AoI) performance in a point-to-point short packet communication system, where a transmitter generates packets based on status updates and transmits the packets to a receiver. Specifically, we investigate three packet management strategies, namely, the non-preemption with no buffer strategy, the non-preemption with one buffer strategy, and the preemption strategy. To characterize the level of the receiver's dissatisfaction on outdated data, we adopt a generalized$\alpha-\beta$AoI penalty function into the analysis and derive closed-form expressions for the average AoI penalty achieved by the three packet management strategies. Simulation results are used to corroborate our analysis and explicitly evaluate the impact of various system parameters, such as the coding rate and status update generation rate, on the AoI performance. Additionally, we find that the value of$\alpha$reflects the system transmission reliability.

We analytically decide whether the broadcast transmission scheme or the unicast transmission scheme achieves the optimal age of information (AoI) performance of a multiuser system where a base station (BS) generates and transmits status updates to multiple user equipments (UEs). In the broadcast transmission scheme, the status update for all UEs is jointly encoded into a packet for transmission, while in the unicast transmission scheme, the status update for each UE is encoded individually and transmitted by following the round robin policy. For both transmission schemes, we examine three packet management strategies, namely the non-preemption strategy, the preemption in buffer strategy, and the preemption in serving strategy. We first derive new closed-form expressions for the average AoI achieved by two transmission schemes with three packet management strategies. Based on them, we compare the AoI performance of two transmission schemes in two systems, namely, the remote control system and the dynamic system. Aided by simulation results, we verify our analysis and investigate the impact of system parameters on the average AoI. For example, the unicast transmission scheme is more appropriate for the system with a large number of UEs. Otherwise, the broadcast transmission scheme is more appropriate.

Reconfigurable intelligent surface (RIS) is able to create favorable reflecting channels for different users and piggyback additional data in the reflected signals. The former brings benefits to non-orthogonal multiple access (NOMA), while the latter enables a mechanism of symbiotic radio (SR). Inspired by these unique advantages, we consider a general SR-NOMA system model where an RIS is deployed to assist both the NOMA in an uplink multi-channel system and the Internet-of-Things (IoT) data transmission. This general model also allows for different performance objectives from the NOMA users. In particular, the users can be either energy-efficiency oriented or spectrum-efficiency oriented. To strike the performance trade-off between these two types of users, a performance metric called resource efficiency (RE) is leveraged to formulate the optimization problem. We jointly design the time-frequency resource allocation, multi-user power control and RIS phase shifts to maximize the weighted sum-RE of the system, subject to the quality-of-service constraints of the SR-NOMA system. An efficient alternating optimization framework with a series of algorithms, including matching theory, fractional programming method, and inner majorization-minimization method, is developed to solve this highly complex and non-convex problem.

This paper presents the first performance analysis of physical layer downlink secure transmissions in a scalable cell-free massive MIMO (SCF-mMIMO) system. A stochastic geometry approach is used to model the locations of the access points (APs), user equipments (UEs) and eavesdroppers (Eves) as independent homogeneous Poisson point processes (HPPPs). In addition to applying maximum ratio transmission (MRT) to send the confidential messages, null-space artificial noise is also injected for secrecy enhancement. We analytically characterize the secrecy performance in terms of both the outage-based secrecy transmission rate (STR) and the ergodic secrecy rate (ESR), appropriate for slow quasi-static fading channels and fast block-fading channels, respectively. By utilizing moment matching and Gil-Pelaez inversion theorem, we are able to obtain mathematically tractable approximations for the performance metrics. These approximations are shown to have high accuracy as compared to simulation results. Our numerical results reveal useful design insights that cannot be inferred from existing studies. These insights answer important questions such as whether it is best to deploy as many APs each with fewer antennas and to what extent the artificial noise insertion is beneficial.

We propose a new spectrum allocation strategy, aided by unsupervised learning, for multiuser terahertz communication systems. In this strategy, adaptive sub-band bandwidth is considered such that the spectrum of interest can be divided into sub-bands with unequal bandwidths. This strategy reduces the variation in molecular absorption loss among the users, leading to the improved data rate performance. We first formulate an optimization problem to determine the optimal sub-band bandwidth and transmit power, and then propose the unsupervised learning-based approach to obtaining the near-optimal solution to this problem. In the proposed approach, we first train a deep neural network (DNN) while utilizing a loss function that is inspired by the Lagrangian of the formulated problem. Then using the trained DNN, we approximate the near-optimal solutions. Numerical results demonstrate that comparing to existing approaches, our proposed unsupervised learning-based approach achieves a higher data rate, especially when the molecular absorption coefficient within the spectrum of interest varies in a highly non-linear manner.

Intelligent reflecting surfaces (IRS) can improve the performance of backscatter communication systems by employing reconfigurable phase shifts (or passive beamforming) to favorably configure the wireless propagation medium. However, the design of optimal IRS phase shifts requires channel state information (CSI), which is hard to acquire in a multi-reflection channel. In this paper, we propose a deep learning based framework that learns the desired IRS phase shifts without knowing the channels, to assist the communication of a passive backscatter tag. This is achieved by parameterizing the mapping from the received pilots to the desired configuration of IRS by training a deep neural network (DNN) BIRS-Net on a sufficiently large dataset covering a variety of channel realizations and possible power splitting ratios at the backscatter tag. Simulation results show that the proposed DNN based solution can efficiently learn to maximize the SNR of backscatter transmission and exhibits near optimal performance.

In this paper, we analyze the impact of different encoding schemes on the age of information (AoI) performance in a point-to-point system, where a source generates packets based on the status updates collected from multiple sensors and transmits the packets to a destination. In this system, we consider two encoding schemes, namely, the joint encoding scheme and the distributed encoding scheme. In the joint encoding scheme, the status updates from all the sensors are jointly encoded into a packet for transmission. In the distributed encoding scheme, the status update from each sensor is encoded individually and the sensors’ packets are transmitted following the round robin policy. To ensure the freshness of packets, the zero-wait policy is adopted in both schemes, where a new packet is immediately generated once the source finishes the transmission of the current packet. We derive closed-form expressions for the average AoI achieved by these two encoding schemes and compare their performances. Simulation results show that the distributed encoding scheme is more appropriate for systems with a relatively large number of sensors, compared with the joint encoding scheme.

We propose to use channel inversion power control (CIPC) to achieve one-way ultra-reliable and lowlatency communications (URLLC), where only the transmission in one direction requires ultra reliability and low latency. Based on channel reciprocity, our proposed CIPC schemes guarantee the power of received signal that is used to decode the information to be a constant value$Q$, by varying the transmit signal and power, which relaxes the assumption of knowing channel state information (CSI) at the user. Thus, the CIPC schemes eliminate the overhead of CSI feedback, reduce communication latency, and explore the benefits of multiple antennas to significantly improve transmission reliability. We derive analytical expressions for the packet loss probability of the proposed CIPC schemes, based on which we determine a closed interval and a convex set for optimizing$Q$in CIPC with imperfect and perfect channel reciprocity, respectively. Our results show that CIPC is an effective means to achieve one-way URLLC. The tradeoff among reliability, latency, and required resources (e.g., transmit antennas) is further revealed, which provides novel principles for designing one-way URLLC systems.

In this paper, we analyze the age of information (AoI) performance of a multi-user mobile edge computing (MEC) system where a base station (BS) generates and transmits computation-intensive packets to user equipments (UEs). In this MEC system, we consider two computing schemes, namely, the local computing scheme and the edge computing scheme. In the local computing scheme, each packet is transmitted to the UE and then computed by the local server at the UE. In the edge computing scheme, each packet is computed by the edge server at the BS and then transmitted to the UE. Considering exponentially distributed transmission time and computation time and adopting the first come first serve queuing policy, we derive the closed-form expressions for the average AoI of these two computing schemes. Simulation results corroborate our analysis and examine the impact of system parameters on the average AoI.

This work investigates the data detection problem in an Intelligent Reflecting Surface (IRS) aided downlink communication between a multi-antenna access point (AP) and multiple user equipments (UEs). We utilise a deep learning-based approach, with a maximum likelihood detection (MLD)-based loss function, thereby bypassing the resource-consuming channel training and estimation requirement for detection. The proposed detection framework first trains a base deep neural network (DNN) offline with the simulated samples of the channel coefficients and IRS phase shifts in the IRS-assisted communications scenario. To deal with the significant challenge of the channel getting outdated, domain adaptation under the transfer learning paradigm is leveraged, i.e., the initial layers of the DNN are frozen, and the remaining layers are retrained on a smaller number of the received signal samples online to account for the channel mismatch. Our results show that the proposed detector achieves BER results close to the lower bound and outperforms conventional benchmark techniques, with relatively lower complexity.

In this article, we propose a two-tier communication strategy to facilitate data collection in unmanned aerial vehicle (UAV)-enabled massive Internet of Things (IoT) systems through introducing ground access points (APs) to serve between the UAV and IoT devices. In the first tier of our proposed strategy, all IoT devices transmit their packets to their local APs via a multi-channel ALOHA-based random access scheme, while in the second tier, APs deliver their aggregated data to the UAV through coordinated time division multiple access. Thus, our introduced APs not only liberate the UAV from the potential massive IoT congestion but also facilitate the design of UAV's trajectory based on the location of APs. To examine the performance of our strategy, we propose a tractable framework to analyze the average system throughput. We reveal that the average two-tier throughput of each AP monotonically increases with its maximum achievable throughput in the second tier, while the increasing slope becomes steeper with a higher traffic load mean in the first tier. Then, we formulate the joint design of UAV's trajectory and resource allocation as a non-convex optimization problem to maximize the average system throughput while considering the heterogeneous quality of service requirement of each AP. To solve this problem, a low-complexity iterative algorithm is devised based on successive convex approximation. Numerical results demonstrate the substantial average system throughput gain achieved by our proposed strategy and design in the context of massive access, compared to the baseline schemes in the literature.

The bistatic backscatter architecture, with its extended range, enables flexible deployment opportunities for backscatter devices. In this paper, we study the placement of power beacons (PBs) in bistatic backscatter networks to maximize the guaranteed coverage distance (GCD), defined as the distance from the reader within which backscatter devices are able to satisfy a given quality-of-service constraint. This work departs from conventional energy source placement problems by considering the performance of the additional backscatter link on top of the energy transfer link. We adopt and optimize a symmetric PB placement scheme to maximize the GCD. The optimal PB placement under this scheme is obtained using either analytically tractable expressions or an efficient algorithm. Numerical results provide useful insights into the impacts of various system parameters on the PB placement and the resulting GCD, plus the advantages of the adopted symmetric placement scheme over other benchmark schemes.

Covert communications enable a transmitter to send information reliably in the presence of an adversary, who looks to detect whether the transmission took place or not. We consider covert communications over quasi-static block fading channels, where users suffer from channel uncertainty. We investigate the adversary Willie's optimal detection performance in two extreme cases, i.e., the case of perfect channel state information (CSI) and the case of channel distribution information (CDI) only. It is shown that in the large detection error regime, Willie's detection performances of these two cases are essentially indistinguishable, which implies that the quality of CSI does not help Willie in improving his detection performance. This result enables us to study the covert transmission design without the need to factor in the exact amount of channel uncertainty at Willie. We then obtain the optimal and suboptimal closed-form solution to the covert transmission design. Our result reveals fundamental difference in the design between the case of quasi-static fading channel and the previously studied case of non-fading AWGN channel.

We introduce a novel system setup where a backscatter device operates in the presence of an intelligent reflecting surface (IRS). In particular, we study the bistatic backscatter communication (BackCom) system assisted by an IRS. The phase shifts at the IRS are optimized jointly with the transmit beamforming vector of the carrier emitter to minimize the transmit power consumption at the carrier emitter whilst guaranteeing a required BackCom performance. The unique channel characteristics arising from multiple reflections at the IRS render the optimization problem highly non-convex. Therefore, we jointly utilize the minorization-maximization algorithm and the semidefinite relaxation technique to present an approximate solution for the optimal IRS phase shift design. We also extend our analytical results to the monostatic BackCom system. Numerical results indicate that the introduction of the IRS brings about considerable reductions in transmit power, even with moderate IRS sizes, which can be translated to range increases over the non-IRS-assisted BackCom system.

We consider uplink machine-type communication (MTC) from energy-constrained devices following the time division multiple access (TDMA) protocol. Conventionally, the energy efficiency performance in TDMA is optimized through multi-user scheduling, i.e., changing the transmission block length allocated to different devices. In such a system, the sequence of devices for transmission, i.e., who transmits first and who transmits second, etc., has not been considered as it does not have any impact on the energy efficiency. In this work, we consider that data compression is performed before transmission and show that the multi-user sequencing is indeed important. We propose to jointly optimize both multi-user sequencing and scheduling along with the compression and transmission rate control. Our results show that multi-user sequence optimization significantly improves the energy efficiency performance of the system, and especially the performance gain is large when the delay bound is stringent. This is advantageous for lower latency MTC.

One of the key challenges of the Internet of Things (IoT) is to sustainably power the large number of IoT devices in real-time. In this paper, we consider a wireless power transfer (WPT) scenario between an energy transmitter (ET) capable of retrodirective WPT and an energy receiver (ER) capable of ambient backscatter in the presence of an ambient source (AS). The ER requests WPT by backscattering signals from an AS towards the ET, which then retrodirectively beamforms an energy signal towards the ER. To remove the inherent directlink ambient interference, we propose a scheme of ambient backscatter training. Specifically, the ER varies the reflection coefficient multiple times while backscattering each ambient symbol according to a certain pattern called the training sequence, whose design criterion we also present. To evaluate the system performance, we derive an analytical expression for the average harvested power at the ER. Our numerical results show that with the proposed scheme, the ER harvests tens of μW of power, without any CSI estimation or active transmission from the ER, which is a significant improvement for low-power and low-cost ambient backscatter devices.

The consideration of unmanned aerial vehicle (UAV) trajectory is of crucial importance in the performance evaluation of cellular-connected UAV networks. In this work, we consider a cellular-connected aerial user equipment (AUE) employed for surveillance and monitoring. The AUE moves along a given trajectory, while periodically transmitting to a terrestrial base station (BS) in the uplink, with a specific quality of service (QoS) requirement. To avoid the underutilization of spectrum resources, we enable simultaneous uplink transmissions of the AUE and a terrestrial user equipment (TUE) using power-domain uplink aerial-terrestrial non-orthogonal multiple access (NOMA). We take the trajectory of AUE into consideration and develop an analytical framework to compute the total rate coverage probability, i.e., the probability where both AUE and TUE are decoded, at a given transmission point in the trajectory. In addition, we numerically determine the minimum height of AUE to achieve a certain QoS constraint for different AUE target data rates and built-up areas. Our results show that, for a spiral trajectory, the minimum height increases as the AUE moves from cell center to the boundary, and as the severity of the environmental parameters increases.

In this paper, we propose joint sequencing and scheduling optimization for uplink machine-type communication (MTC). We consider multiple energy-constrained MTC devices that transmit data to a base station following the time division multiple access (TDMA) protocol. Conventionally, the energy efficiency performance in TDMA is optimized through multi-user scheduling, i.e., changing the transmission block length allocated to different devices. In such a system, the sequence of devices for transmission, i.e., who transmits first and who transmits second, etc., has not been considered as it does not have any impact on the energy efficiency. In this work, we consider that data compression is performed before transmission and show that the multi-user sequencing is indeed important. We apply three popular energy-minimization system objectives, which differ in terms of the overall system performance and fairness among the devices. We jointly optimize both multi-user sequencing and scheduling along with the compression and transmission rate control. Our results show that multi-user sequence optimization significantly improves the energy efficiency performance of the system. Notably, it makes the TDMA-based multi-user transmissions more likely to be feasible in the lower latency regime, and the performance gain is larger when the delay bound is stringent.

This paper considers an emerging cellular-connected unmanned aerial vehicle (UAV) architecture for surveillance or monitoring applications. We study a scenario of interest where a cellular-connected aerial user equipment (AUE) periodically transmits in uplink to a base station (BS) with a given data rate requirement, while moving along a given trajectory. For an efficient spectrum usage, we enable the concurrent uplink transmission of the AUE and a terrestrial user equipment (TUE) by employing power-domain aerial-terrestrial non-orthogonal multiple access (NOMA), while accounting for the AUE's known trajectory. To characterize the system performance, we develop an analytical framework to compute the rate coverage probability, i.e., the probability that the achievable data rate of both the AUE and TUE exceeds the respective target rates. We use our analytical results to numerically determine the minimum height that the AUE needs to fly, at each transmission point along the given trajectory, in order to satisfy a certain quality of service (QoS) constraint of various AUE target data rates in different built-up environments. Specifically, our results show that the minimum height of the AUE depends on its distance from the BS as the AUE moves along the given trajectory which indicates the importance of modeling AUE trajectory in cellular-connected UAV systems.

Wireless power transfer (WPT) using energy beamforming is a promising solution for low power Internet of Things (IoT) devices. In this work, we consider WPT from an energy transmitter (ET) employing retrodirective WPT using a large phased antenna array to an energy receiver (ER) capable of ambient backscatter. The advantage of retrodirective WPT is that no explicit channel estimation is needed at the ET and the use of ambient backscattering eliminates the need for active transmission at the ER. We propose a training sequence design, i.e., pattern of varying the reflection coefficient at the ER, to eliminate the direct-link interference from the ambient source. We show that when the ambient symbol duration is known, the ambient interference is fully cancelled by the proposed design. We analytically model the system and find the average harvested power at the ER considering Nakagami-m fading channels and non-linear energy harvesting model. Our results clearly show that the proposed solution is robust to a small timing offset mismatch at the correlator. When interference from undesired neighbouring sources in the ambient environment is not significant, the ER can successfully harvest tens to hundreds of μW of power, which is an important improvement for low-power IoT devices.

We consider the use of a backscatter device as a relay, and examine a new decode-and-forward (DF) scheme specifically designed for backscatter relaying. In the proposed scheme, the source node transmits continuous-wave (CW) signals to power the backscatter relay in the relay-to-destination phase of the data transmission. We characterise the end-to-end bit error rate (BER) performance for on-off keying (OOK) modulation. In addition, we formulate and solve a power allocation problem at the source node, where the source is subject to a power budget constraint. Numerical results show that the relay-to-destination link is the bottleneck for the end-to-end performance; and that it is essential to allocate most of the source's power budget to its transmission of CW signals to power the relay's transmission.

This work considers the design of online transmission policy in a wireless-powered communication system with a given energy budget. The system design objective is to maximize the long-term throughput of the system exploiting the energy storage capability at the wireless-powered node. We formulate the design problem as a constrained Markov decision process (CMDP) problem and obtain the optimal policy of transmit power and time allocation in each fading block via the Lagrangian approach. To investigate the system performance in different scenarios, numerical simulations are conducted with various system parameters. Our simulation results show that the optimal policy significantly outperforms a myopic policy which only maximizes the throughput in the current fading block. Moreover, the optimal allocation of transmit power and time is shown to be insensitive to the change of modulation and coding schemes, which facilitates its practical implementation.

Covert communication in backscatter radio systems is considered, where the transmitter controls its transmit power to keep the transponder's response hidden, while a warden tries to detect this covert communication. To achieve covertness, we propose a non-conventional transmission scheme where the transmitter emits noise-like signal with transmit power varying across different communication slots. Under the assumption of a radiometer as the detector at the warden, we first derive the optimal detection threshold for this detector. Next, building upon the detection performance of warden, we analyze the condition on the transmit power to achieve a target level of covertness. Our numerical results illustrate the price a backscatter system has to pay, in terms of bit error rate, for achieving covert communication.

While Gaussian signalling is assumed in many studies on covert communications, its optimality has not been carefully investigated. In this work, we examine this optimality by considering the approach of upper bounding D(p0(y)∥p1(y)) as the covert communication constraint, where D(p0(y)∥p1(y)) is the Kullback-Leibler divergence from p0(y) to p1(y), p0(y) and p1(y) are the likelihood functions of the observation y at the warden under the null hypothesis (no covert transmission) and alternative hypothesis (a covert transmission occurs), respectively. Considering additive white Gaussian noise at both the receiver and the warden, we prove that Gaussian signalling is not optimal in terms of maximizing the mutual information of transmitted and received signals for covert communications with D(p0(y)∥p1(y)) ≤ 2ϵ2as the constraint. We also explicitly show a skew-normal signalling can outperform Gaussian signalling in terms of achieving higher mutual information subject to the same covertness constraint D(p0(y)∥p1(y)) ≤ 2ϵ2.

We consider a machine-type communication (MTC) node that is served by a hybrid access point (HAP) which provides RF power transfer to the node and receives data transmission from the node. Due to the lossy wireless medium and limited efficiency of RF energy transducer, the energy cost at the HAP is substantial. To minimize the energy cost while still satisfying the system requirement, the harvested energy at the MTC node must be used efficiently. To this end, we consider that the MTC node employs data compression in order to reduce the energy cost of data transmission. Data compression itself consumes time and energy, which needs to be carefully controlled. Thus, we propose to jointly optimize the harvesting-time, compression and transmission design, to minimize the energy cost of the system under given delay constraint. The proposed scheme achieves up to 19% performance gain, under given system constraints, as compared to optimizing harvesting-time ratio and transmission rate without employing compression.

In this paper, we study delay-intolerant covert communications in additive white Gaussian noise (AWGN) channels with a finite block length, i.e., a finite number of channel uses. Considering the maximum allowable number of channel uses to be N, it is not immediately clear whether the actual number of channel uses, denoted by n, should be as large as N or smaller for covert communications. This is because a smaller n reduces a warden's chance to detect the communications due to fewer observations, but also reduces the chance to transmit information. We show that n = N is indeed optimal to maximize the amount of information bits that can be transmitted, subject to any covert communication constraint in terms of the warden's detection error probability. To better make use of the warden's uncertainty due to the finite block length, we also propose to use uniformly distributed random transmit power to enhance covert communications. Our examination shows that the amount of information that can be covertly transmitted logarithmically increases with the number of random power levels, which indicates that most of the benefit of using random transmit power is achieved with just a few different power levels.

In this paper, we consider the design of online transmission policies in a single-user wireless-powered communication system over an infinite horizon, aiming at maximizing the long-term system throughput for the user equipment (UE) subject to a given energy budget. The problem is formulated as a constrained Markov decision process problem, which is subsequently converted into an equivalent Markov decision process (MDP) problem via the Lagrangian approach. The corresponding optimal resource allocation policy is obtained through jointly solving the corresponding MDP problem and updating the Lagrangian multiplier. To reduce the complexity, a sub-optimal policy named “quasi-best-effort” is proposed, where the transmit power of the UE is structurally designed so that in each block the UE either exhausts its entire battery energy for transmission or suspends its transmission. To validate the effectiveness of our proposed policy, extensive numerical simulations are conducted with various system parameters. The results show that the proposed quasi-best-effort policy requires far less computation time but achieves a similar long-term throughput performance as the optimal policy.

In this paper, we examine the optimality of Gaussian signalling for covert communications with an upper bound on D(p1||p0) or D(p0||p1) as the covertness constraint, where D(p1||p0) and D(p0||p1) are different due to the asymmetry of Kullback-Leibler divergence, p0(y) and p1(y) are the likelihood functions of the observation y at the warden under the null hypothesis (no covert transmission) and alternative hypothesis (a covert transmission occurs), respectively. Considering additive white Gaussian noise at both the receiver and the warden, we prove that the Gaussian signalling is optimal in terms of maximizing the mutual information of transmitted and received signals for covert communications with an upper bound on D(p1||p0) as the constraint. More interestingly, we also prove that the Gaussian signalling is not optimal for covert communications with an upper bound on D(p0||p1) as the constraint, for which as we explicitly show skew-normal signalling can outperform the Gaussian signalling in terms of achieving higher mutual information. Finally, we prove that, for Gaussian signalling, an upper bound on D(p1||p0) is a tighter covertness constraint in that it leads to lower mutual information than the same upper bound on D(p0||p1), by proving D(p0||p1) ≤ D(p1||p0).

For a sensor based machine-type communication (MTC) device, transmission is a power hungry operation and blindly applying too much data compression may even exceed the cost of transmitting raw data, thus losing its purpose. Hence, it is important to investigate the trade-off between data compression and transmission energy costs. We consider a system that is composed of an energy constrained sensor based MTC device and a sink node, and devise an optimal data compression and transmission policy with an objective to maximize the lifetime of the sensor based MTC device whilst satisfying specific delay and bit error rate (BER) constraints when statistical channel gain is known at the sensor node. Our results show that a jointly optimized compression-transmission policy achieves 100% to 1500% better performance as compared to optimizing transmission only without compression under given BER and delay constraints. Importantly, the gain is most profound in the low latency regime.

In this work, we propose a covert communication scheme where the transmitter attempts to hide its transmission to a full-duplex receiver, from a warden that is to detect this covert transmission using a radiometer. Specifically, we first derive the detection error rate at the warden, based on which the optimal detection threshold for its radiometer is analytically determined and its expected detection error rate over wireless fading channels is achieved in a closed-form expression. Our analysis indicates that the artificial noise deliberately produced by the receiver with a random transmit power, although causes self-interference, offers the capability of achieving a positive effective covert rate for any transmit power (can be infinity) subject to any given covertness requirement on the expected detection error rate. This work is the first study on the use of the full- duplex receiver with controlled artificial noise for achieving covert communications and invites further investigation in this regard.

The fifth generation of mobile communications (5G) is expected to exploit the concept of location-aware communication systems. Therefore, there is a need to understand the localization limits in these networks, particularly, using millimeter-wave technology (mmWave). Contributing to this understanding, we consider single-anchor localization limits in terms of 3D position and orientation error bounds for mmWave multipath channels, for both the uplink and downlink. It is found that uplink localization is sensitive to the orientation angle of the user equipment (UE), whereas downlink is not. Moreover, in the considered outdoor scenarios, reflected and scattered paths generally improve localization. Finally, using detailed numerical simulations, we show that mmWave systems are in theory capable of localizing a UE with sub-meter position error, and sub-degree orientation error.

This paper proposes a new channel training (CT) scheme for a full-duplex receiver to enhance physical layer security. Equipped with NBfull-duplex antennas, the receiver simultaneously receives the information signal and transmits artificial noise (AN). In order to reduce the non-cancellable self-interference due to the transmitted AN, the receiver has to estimate the self-interference channel prior to the data communication phase. In the proposed CT scheme, the receiver transmits a limited number of pilot symbols that are known only to itself. Such a secret CT scheme prevents an eavesdropper from estimating the jamming channel from the receiver to the eavesdropper, hence effectively degrading the eavesdropping capability. We analytically examine the connection probability (i.e., the probability of the data being successfully decoded by the receiver) of the legitimate channel and the secrecy outage probability due to eavesdropping for the proposed secret CT scheme. Based on our analysis, the optimal power allocation between CT and data/AN transmission at the legitimate transmitter/receiver is determined. Our examination shows that the newly proposed secret CT scheme significantly outperforms the non-secret CT scheme that uses publicly known pilots when the number of antennas at the eavesdropper is larger than one.

Location-aware communication systems are expected to play a pivotal part in the next generation of mobile communication networks. Therefore, there is a need to understand the localization limits in these networks, particularly, using millimeter-wave technology (mm-wave). Towards that, we address the uplink and downlink localization limits in terms of 3D position and orientation error bounds for mm-wave multipath channels. We also carry out a detailed analysis of the dependence of the bounds on different system parameters. Our key findings indicate that the uplink and downlink behave differently in two distinct ways. First of all, the error bounds have different scaling factors with respect to the number of antennas in the uplink and downlink. Secondly, uplink localization is sensitive to the orientation angle of the user equipment (UE), whereas downlink is not. Moreover, in the considered outdoor scenarios, the non-line-of-sight paths generally improve localization when a line-of-sight path exists. Finally, our numerical results show that mm-wave systems are capable of localizing a UE with sub-meter position error, and sub-degree orientation error.

We consider a system that is composed of an energy constrained sensor node and a sink node, and devise optimal data compression and transmission policies with an objective to prolong the lifetime of the sensor node. While applying compression before transmission reduces the energy consumption of transmitting the sensed data, blindly applying too much compression may even exceed the cost of transmitting raw data, thereby losing its purpose. Hence, it is important to investigate the trade-off between data compression and transmission energy costs. In this paper, we study the joint optimal compression-transmission design in three scenarios which differ in terms of the available channel information at the sensor node, and cover a wide range of practical situations. We formulate and solve joint optimization problems aiming to maximize the lifetime of the sensor node whilst satisfying specific delay and bit error rate constraints. Our results show that a jointly optimized compression-transmission policy achieves significantly longer lifetime (90% to 2000%) as compared to optimizing transmission only without compression. Importantly, this performance advantage is most profound when the delay constraint is stringent, which demonstrates its suitability for low latency communication in future wireless networks.

Backscatter communication (BackCom), which allows a backscatter node (BN) to communicate with the reader by modulating and reflecting the incident continuous wave from the reader, is considered a promising solution to power the future Internet-of-Things. In this paper, we consider a single BackCom system, where multiple BNs are served by a reader. We propose using the power-domain non-orthogonal multiple access (NOMA), i.e., multiplexing the BNs in different regions or with different backscattered power levels, to enhance the spectrum efficiency of the BackCom system. To better exploit power-domain NOMA, we propose setting the reflection coefficients for multiplexed BNs to be different. Based on this considered model, we develop the reflection coefficient selection criteria. To illustrate the enhanced system with the proposed criteria, we analyze the performance of the BackCom system in terms of the average number of bits that can be successfully decoded by the reader for the two-node pairing case and the average number of successful BNs for the general multiplexing case. Our results show that NOMA achieves the much better performance gain in the BackCom system as compared to its performance gain in the conventional system, which highlights the importance of applying NOMA to the BackCom system.

In this paper, we study covert communication in wireless networks consisting of a transmitter, Alice, an intended receiver, Bob, a warden, Willie, and a Poisson field of interferers. Bob and Willie are subject to uncertain shot noise due to the ambient signals from interferers in the network. With the aid of stochastic geometry, we analyze the throughput of the covert communication between Alice and Bob subject to given requirements on the covertness against Willie and the reliability of decoding at Bob. We consider non-fading and fading channels. We analytically obtain interesting findings on the impacts of the density and the transmit power of the concurrent interferers on the covert throughput. That is, the density and the transmit power of the interferers have no impact on the covert throughput as long as the network stays in the interference-limited regime, for both the non-fading and the fading cases. When the interference is sufficiently small and comparable with the receiver noise, the covert throughput increases as the density or the transmit power of the concurrent interferers increases.

Covert wireless communication aims to hide the very existence of wireless transmissions in order to guarantee a strong security in wireless networks. In this paper, we examine the possibility and achievable performance of covert communication in amplify-and-forward one-way relay networks. Specifically, the relay is greedy and opportunistically transmits its own information to the destination covertly on top of forwarding the source's message, while the source tries to detect this covert transmission to discover the illegitimate usage of the resource (e.g., power and spectrum) allocated only for the purpose of forwarding the source's information. We propose two strategies for the relay to transmit its covert information, namely rate-control and power-control transmission schemes, for which the source's detection limits are analyzed in terms of detection error probability and the achievable effective covert rates from the relay to destination are derived. Our examination determines the conditions under which the rate-control transmission scheme outperforms the power-control transmission scheme, and vice versa, which enables the relay to achieve the maximum effective covert rate. Our analysis indicates that the relay has to forward the source's message to shield its covert transmission and the effective covert rate increases with its forwarding ability (e.g., its maximum transmits power).

Covert communications hide the transmission of a message from a watchful adversary while ensuring a certain decoding performance at the receiver. In this paper, a wireless communication system under fading channels is considered where covertness is achieved by using a full-duplex receiver. More precisely, the receiver of covert information generates artificial noise with a varying power causing uncertainty at the adversary, Willie, regarding the statistics of the received signals. Given that Willie's optimal detector is a threshold test on the received power, we derive a closed-form expression for the optimal detection performance of Willie averaged over the fading channel realizations. Furthermore, we provide guidelines for the optimal choice of artificial noise power range, and the optimal transmission probability of covert information to maximize the detection errors at Willie. Our analysis shows that the transmission of artificial noise, although causing self-interference, provides the opportunity of achieving covertness but its transmit power levels need to be managed carefully. We also demonstrate that the prior transmission probability of 0.5 is not always the best choice for achieving the maximum possible covertness when the covert transmission probability and artificial noise power can be jointly optimized.

This paper studies the design and secrecy performance of linear multihop networks, in the presence of randomly distributed eavesdroppers in a large-scale 2-D space. Depending on whether there is feedback from the receiver to the transmitter, we study two transmission schemes: an ON–OFF transmission (OFT) and a non-ON–OFF transmission (NOFT). In the OFT scheme, transmission is suspended if the instantaneous received signal-to-noise ratio (SNR) falls below a given threshold, whereas, there is no suspension of transmission in the NOFT scheme. We investigate the optimal design of the linear multiple network in terms of the optimal rate parameters of the wiretap code as well as the optimal number of hops. These design parameters are highly interrelated, since more hops reduce the distance of per-hop communication, which completely changes the optimal design of the wiretap coding rates. Despite the analytical difficulty, we are able to characterize the optimal designs and the resulting secure transmission throughput in mathematically tractable forms in the high SNR regime. Our numerical results demonstrate that our analytical results obtained in the high SNR regime are accurate at practical SNR values. Hence, these results provide useful guidelines for designing linear multihop networks with targeted physical layer security performance.

Enabling machine-type communication (MTC) over large scale cellular networks is a promising solution to handling the emerging MTC traffic. To enable a massive number of machines to connect to the base station, random access mechanisms and data aggregation have been largely studied separately in the literature. In this paper, we use stochastic geometry to investigate MTC over cellular with access class barring enhanced random access and data aggregation. We present an approximate yet accurate and tractable analytical framework for characterizing the MTC performance in terms of the machine type device (MTD) success probability, average number of successful MTDs and probability of successful preamble utilization. We validate the proposed model by comparison with simulations. Our results show that while the provision of more resources for the relaying phase benefits MTC, the provision of more preambles in the random access is not always beneficial to MTC. Thus, system parameters need to be chosen carefully to benefit the MTC traffic.

Covert communication aims to shield the very existence of wireless transmissions in order to guarantee a strong security in wireless networks. In this work, for the first time we examine the possibility and achievable performance of covert communication in one- way relay networks. Specifically, the relay opportunistically transmits its own information to the destination covertly on top of forwarding the source's message, while the source tries to detect this covert transmission to discover the illegitimate usage of the recourse (e.g., power, spectrum) allocated only for the purpose of forwarding source's information. The necessary condition that the relay can transmit covertly without being detected is identified and the source's detection limit is derived in terms of the false alarm and miss detection rates. Our analysis indicates that boosting the forwarding ability of the relay (e.g., increasing its maximum transmit power) also increases its capacity to perform the covert communication in terms of achieving a higher effective covert rate subject to some specific requirement on the source's detection performance.

Future Internet-of-Things (IoT) is expected to wirelessly connect tens of billions of low- complexity devices. Extending the finite battery life of massive number of IoT devices is a crucial challenge. The ultra-low-power backscatter communications (BackCom) with the inherent feature of RF energy harvesting is a promising technology for tackling this challenge. Moreover, many future IoT applications will require the deployment of dense IoT devices, which induces strong interference for wireless information transfer (IT). To tackle these challenges, in this paper, we propose the design of a novel multiple-access scheme based on time-hopping spread-spectrum (TH-SS) to simultaneously suppress interference and enable both two-way wireless IT and one-way wireless energy transfer (ET) in coexisting backscatter reader-tag links. The performance analysis of the BackCom network is presented, including the bit-error rates for forward and backward IT and the expected energy-transfer rate for forward ET, which account for non-coherent and coherent detection at tags and readers, and energy harvesting at tags, respectively. Our analysis demonstrates a tradeoff between energy harvesting and interference performance. Thus, system parameters need to be chosen carefully to satisfy given BackCom system performance requirement.

Covert communication is to achieve a reliable transmission from a transmitter to a receiver while guaranteeing an arbitrarily small probability of this transmission being detected by a warden. In this work, we study the covert communication in AWGN channels with finite blocklength, in which the number of channel uses is finite. Specifically, we analytically prove that the entire block (all available channel uses) should be utilized to maximize the effective throughput of the transmission subject to a predetermined covert requirement. This is a nontrivial result because more channel uses results in more observations at the warden for detecting the transmission. We also determine the maximum allowable transmit power per channel use, which is shown to decrease as the blocklength increases. Despite the decrease in the maximum allowable transmit power per channel use, the maximum allowable total power over the entire block is proved to increase with the blocklength, which leads to the fact that the effective throughput increases with the blocklength.

In this work, we propose a new channel training (CT) scheme to enhance physical layer security in a full-duplex wiretap channel, where the multi-antenna and full-duplex receiver simultaneously receives the information signal and transmits artificial noise (AN). In order to suppress the self-interference caused by AN, the receiver has to estimate the self-interference channel prior to the data communication phase. In the proposed CT scheme, the receiver transmits limited pilot symbols which are known only to itself, which prevents the eavesdropper from estimating the jamming channel from the receiver to the eavesdropper, hence effectively degrades the eavesdropping capability. Compared with the traditional CT scheme that uses publicly known pilots, the newly proposed secret CT scheme offers significantly better performance when the number of antennas at the eavesdropper is larger than one, e.g., Ne> 1. The optimal power allocation between CT and data/AN transmission at the legitimate transmitter/receiver is determined for the proposed secret CT scheme.

In this paper, we consider underlay in-band device-to-device (D2D) communication in a finite cellular network region. To minimize the D2D interference generated at the base station (BS), we adopt the exclusion zone mechanism, i.e., only D2D users outside the BS exclusion zone share the same resource with the cellular uplink user. Using the stochastic geometry, we develop a general framework to analytically compute the outage probability at the center-located BS and the outage probability at an arbitrarily located D2D receiver in a disk-shaped network region. To quantify the overall D2D communication performance in the finite region, the average number of successful D2D transmissions is also derived. It shows that the D2D receiver close to the cell edge or the exclusion zone experiences lower outage probability compared to the D2D receiver not close to the edge region, which illustrates the location-dependent performance. Moreover, given the outage probability constraint at the BS, which is controlled by varying the radius of the exclusion zone, we find that there is an optimum D2D receiver sensitivity that results in the maximum average number of successful D2D transmissions. The results highlight the importance of carefully choosing system parameters to extract the benefit from the exclusion zone.

Increasing densification in future wireless networks means that user association will play an ever more critical role in the network decision process in order to manage the large number of base stations and users. Though conventional user association aims to maximize a sum rate or capacity related objective, user rate fairness could become a more important consideration for dense networks. In this paper, we propose a downlink base station preference association scheme where users connect to the base station where it is most preferred in terms of the maximum received power. We prove analytically that this scheme results in roughly the same number of users associated to each base station regardless of base station transmit power, and will result in high user rate fairness in dense networks. In addition, we study how the associations change with network dynamics, i.e., users entering and exiting the network (e.g., due to users crossing boundaries of small cells) or base stations entering and exiting the network (e.g., due to base station switching ON or OFF to reduce energy consumption). Our results show that there exists a type of user most likely to re-associate, and that a shrinking network leads to more re-association than a growing one.

A covert communication system under block fading channels is considered, where users experience uncertainty about their channel knowledge. The transmitter seeks to hide the covert communication to a private user by exploiting a legitimate public communication link, while the warden tries to detect this covert communication by using a radiometer. We derive the exact expression for the radiometer's optimal threshold, which determines the performance limit of the warden's detector. Furthermore, for given transmission outage constraints, the achievable rates for legitimate and covert users are analyzed, while maintaining a specific level of covertness. Our numerical results illustrate how the achievable performance is affected by the channel uncertainty and required level of covertness.

To enable massive machine type communication (mMTC), data aggregation is a promising approach to reduce the congestion caused by a massive number of machine type devices (MTDs). In this paper, we consider a two-phase cellular-based mMTC network, where MTDs transmit to aggregators (i.e., aggregation phase) and the aggregated data is then relayed to base stations (i.e., relaying phase). Due to the limited resources, the aggregators not only aggregate data, but also schedule resources among MTDs. We consider two scheduling schemes: random resource scheduling (RRS) and channel-aware resource scheduling (CRS). By leveraging the stochastic geometry, we present a tractable analytical framework to investigate the signal-to-interference ratio (SIR) for each phase, thereby computing the MTD success probability, the average number of successful MTDs and probability of successful channel utilization, which are the key metrics characterizing the overall mMTC performance. Our numerical results show that, although the CRS outperforms the RRS in terms of SIR at the aggregation phase, the simpler RRS has almost the same performance as the CRS for most of the cases with regards to the overall mMTC performance. Furthermore, the provision of more resources at the aggregation phase is not always beneficial to the mMTC performance.

In this paper, we propose a novel splitting receiver, which involves a joint processing of coherently and non-coherently received signals. Using a passive RF power splitter, the received signal at each receiver antenna is split into two streams, which are then processed by a conventional coherent detection (CD) circuit and a power-detection (PD) circuit, respectively. The streams of the signals from all the receiver antennas are then jointly used for information detection. We show that the splitting receiver creates a 3-D received signal space due to the joint coherent and non-coherent processing. We analyze the achievable rate of a splitting receiver, which shows that the splitting receiver provides a rate gain of 3/2 compared with either the conventional (CD-based) coherent receiver or the PD-based non-coherent receiver in the high SNR regime. We also analyze the symbol error rate (SER) for practical modulation schemes, which shows that the splitting receiver achieves asymptotic SER reduction by a factor of at least √M-1 for M-QAM compared with either the conventional (CD-based) coherent receiver or the PD-based non-coherent receiver.

This paper studies an online algorithm for an energy harvesting transmitter, where the transmission (completion) time is considered as the system performance. Unlike the existing online algorithms, which more or less require knowledge on the future behavior of the energy-harvesting rate, we consider a practical but significantly more challenging scenario, where the energy-harvesting rate is assumed to be totally unknown. Our design is formulated as a robust-optimal control problem, which aims to optimize the worst-case performance. The transmit power is designed based only on the current battery energy level and the data queue length directly monitored by the transmitter itself. Specifically, we apply an event-trigger approach, in which the transmitter continuously monitors the battery energy and triggers an event when a significant change occurs. Once an event is triggered, the transmit power is updated according to the solution to the robust-optimal control problem, which is given in a simple analytic form. We present numerical results on the transmission time achieved by the proposed design and demonstrate its robust-optimality.

This paper studies a wireless network consisting of multiple transmitter-receiver pairs where interference is treated as noise. Previously, the throughput region of such networks was characterized for either one time slot or an infinite time horizon. We aim to fill the gap by investigating the throughput region for transmissions over a finite time horizon. Unlike the infinite-horizon throughput region, which is simply the convex hull of the throughput region of one time slot, the finite-horizon throughput region is generally non-convex. Instead of directly characterizing all achievable rate-tuples in the finite-horizon throughput region, we propose a metric termed the rate margin, which not only determines whether any given rate-tuple is within the throughput region (i.e., achievable or unachievable), but also tells the amount of scaling that can be done to the given achievable (unachievable) rate-tuple such that the resulting rate-tuple is still within (brought back into) the throughput region. Furthermore, we derive an efficient algorithm to find the rate-achieving policy for any given rate-tuple in the finite-horizon throughput region.

Underlay in-band device-to-device (D2D) communication can improve the spectrum efficiency of cellular networks. However, the coexistence of D2D and cellular users causes inter-cell and intra-cell interference. The former can be effectively managed through inter-cell interference coordination and, therefore, is not considered in this paper. Instead, we focus on the intra-cell interference and propose a D2D mode selection scheme to manage it inside a finite cellular network region. The potential D2D users are controlled by the base station (BS) to operate in D2D mode based on the average interference generated to the BS. Using stochastic geometry, we study the outage probability experienced at the BS and a D2D receiver, and spectrum reuse ratio, which quantifies the average fraction of successfully transmitting D2D users. The analysis shows that the outage probability at the D2D receiver varies for different locations. In addition, without impairing the performance at the BS, if the path-loss exponent on the cellular link is slightly lower than that on the D2D link, the spectrum reuse ratio can have negligible decrease, while the D2D users' average number of successful transmissions increases with increasing D2D node density. This indicates that an increasing level of D2D communication can be beneficial in future networks.

We design a novel artificial-noise-aided secure ON-OFF transmission scheme in a wiretap channel. We consider a practical scenario, where the multi-antenna transmitter only obtains partial channel knowledge from the single-antenna receiver through limited training and feedback but has no channel knowledge about the single-antenna eavesdropper. In the design, we first propose a three-period block transmission protocol to capture the practical training and quantization features. We then characterize the statistics of the received signal-to-noise ratios at the receiver and the eavesdropper. Under the secrecy outage constraint, we exploit the ON-OFF scheme to perform secure transmission and derive a closed-form expression for the secrecy throughput. Moreover, we investigate the optimization problem of maximizing the secrecy throughput by proposing an iterative algorithm to determine the optimal power allocation between the information signal and artificial noise, as well as the optimal codeword transmission rate. Furthermore, we define the net secrecy throughput (NST), which takes the signaling overhead into account and address the problem of optimally allocating the block resource to the training and feedback overhead. Numerical results clearly demonstrate how the optimal signaling overhead changes with the number of transmit antennas, and there exists an optimal number of antennas that maximizes the NST.

Future Internet-of-Things (IoT) is expected to wirelessly connect billions of low-complexity devices. For wireless information transfer (IT) in IoT, high density of IoT devices and their ad hoc communication result in strong interference, which acts as a bottleneck on wireless IT. Furthermore, battery replacement for the massive number of IoT devices is difficult if not infeasible, making wireless energy transfer (ET) desirable. This motivates: 1) the design of full-duplex wireless IT to reduce latency and enable efficient spectrum utilization and 2) the implementation of passive IoT devices using backscatter antennas that enable wireless ET from one device (reader) to another (tag). However, the resultant increase in the density of simultaneous links exacerbates the interference issue. This issue is addressed in this paper by proposing the design of full-duplex backscatter communication (BackCom) networks, where a novel multiple-access scheme based on time-hopping spread-spectrum is designed to enable both one-way wireless ET and two-way wireless IT in coexisting backscatter reader-tag links. Comprehensive performance analysis of BackCom networks is presented in this paper, including forward/backward bit-error rates and wireless ET efficiency and outage probabilities, which accounts for energy harvesting at tags, non-coherent and coherent detection at tags and readers, respectively, and the effects of asynchronous transmissions.

Information-theoretical approaches can ensure security, regardless of the computational power of the attackers. Requirements for the application of this theory are: 1) assuring an advantage over the eavesdropper quality of reception and 2) knowing where the eavesdropper is. The traditional metrics are the secrecy capacity or outage, which are both related to the quality of the legitimate link against the eavesdropper link. Our goal is to define a new metric, which is the characteristic of the security of the surface/environment where the legitimate link is immersed, regardless of the position of the eavesdropping node. The contribution of this paper is twofold: 1) a general framework for the derivation of the secrecy capacity of a surface, which considers all the parameters that influence the secrecy capacity and 2) the definition of a new metric to measure the secrecy of a surface: the secrecy pressure. The metric can be also visualized as a secrecy map, analogously to weather forecast. Different application scenarios are shown: from “forbidden zone” to Gaussian mobility model for the eavesdropper. Moreover, the secrecy outage probability of a surface is derived. This additional metric can measure, which is the secrecy rate supportable by the specific environment.

The utilization of the millimeter-wave frequency band (mm-wave) in the fifth generation ({5G}) of mobile communication is a highly-debated current topic. Mm-wave MIMO systems will use arrays with large number of antennas at the transmitter and the receiver, implemented on a relatively small area. With the inherent high directivity of these arrays, algorithms to help the user equipment find the base station and establish a communication link should be carefully designed. Towards that, we examine two beamforming schemes, namely, random-phase beamforming (RPBF) and directional beamforming (DBF), and test their impact on the Cram\'er-Rao lower bounds (CRB) of jointly estimating the direction-of-arrival, direction-of-departure, time-of-arrival, and the complex channel gain, under the line-of-sight channel model. The results show that the application of RPBF is more appropriate in the considered scenario as it attains a lower CRB with fewer beams compared to DBF.

This paper investigates the offline packet-delay-minimization problem for an energy harvesting transmitter. To overcome the non-convexity of the problem, we propose a C2-diffeomorphic transformation and provide the necessary and sufficient condition for the transformed problem to a standard convex optimization problem. Based on this condition, a simple choice of the transformation is determined which allows an analytically tractable solution of the original non-convex problem to be easily obtained once the transformed convex problem is solved. We further study the structure of the optimal transmission policy in a special case and find it to follow a weighted-directional-water-filling structure. In particular, the optimal policy tends to allocate more power in earlier time slots and less power in later time slots. Our analytical insight is verified by simulation results.

This paper studies a wireless network consisting of multiple transmitter-receiver pairs sharing the same spectrum where interference is regarded as noise. Previously, the throughput region of such a network was characterized for either one time slot or an infinite time horizon. This work aims to close the gap by investigating the throughput region for transmissions over a finite time horizon. We derive an efficient algorithm to examine the achievability of any given rate in the finite-horizon throughput region and provide the rate-achieving policy. The computational efficiency of our algorithm comes from the use of A* search with a carefully chosen heuristic function and a tree pruning strategy. We also show that the celebrated max-weight algorithm which finds all achievable rates in the infinite-horizon throughput region fails to work for the finite-horizon throughput region.

We examine for the first time the impact of transmitter-side correlation on the secure transmission with artificial noise (AN), based on which a new power allocation strategy for AN is devised for physical layer security enhancement. Specifically, we design a correlation-based power allocation (CPA) for AN, of which the optimality in terms of achieving the minimum secrecy outage probability is analytically proved in the large system regime with the number of transmit antennas approaching infinity. Our numerical results demonstrate that CPA is nearly optimal and can significantly outperform the widely-used uniform power allocation (UPA) even for a moderate (finite) number of correlated transmit antennas. Our numerical results also reveal a fundamental difference between the secrecy performance of CPA and that of UPA. When the number of correlated transmit antennas increases, we find that the secrecy outage probability of CPA always reduces while the secrecy outage probability of UPA suffers from a saturation point.

In this paper, we study secure transmission designs for underlay cognitive radio networks in the present of randomly distributed eavesdroppers. We consider the scenario where a secondary transmitter sends confidential messages to a secondary receiver subject to an interference constraint set by the primary user. We design two transmission protocols under different channel knowledge assumptions at the transmitter. For each protocol, we first give a comprehensive performance analysis to investigate the transmission delay, secrecy, and reliability performance. We then optimize the transmission design for maximizing the secrecy throughput subject to both secrecy and reliability constraints. Finally, we numerically compare the performance of the two transmission protocols.

In this paper, we investigate the performance of simultaneous wireless information and power transfer (SWIPT) in a point-to-point system, adopting practical M-ary modulation. We take into account the fact that the receiver's radio-frequency (RF) energy harvesting circuit can only harvest energy when the received signal power is greater than a certain sensitivity level. For both power-splitting (PS) and time-switching (TS) schemes, we derive the energy harvesting performance as well as the information decoding performance for the Nakagami-m fading channel. We also analyze the performance tradeoff between energy harvesting and information decoding by studying an optimization problem, which maximizes the information decoding performance and satisfies a constraint on the minimum harvested energy. Our analysis shows that (i) for the PS scheme, modulations with high peak-to-average power ratio achieve better energy harvesting performance, (ii) for the TS scheme, it is desirable to concentrate the power for wireless power transfer in order to minimize the non-harvested energy caused by the RF energy harvesting sensitivity level, and (iii) channel fading is beneficial for energy harvesting in both PS and TS schemes.

This paper proposes a centralized decision making framework at the macro base station (MBS) for device-to-device (D2D) communication underlaying a two-tier cellular network. We consider a D2D pair in the presence of an MBS and a femto access point, each serving a user, with quality of service constraints for all users. Our proposed solution encompasses mode selection (choosing between cellular or reuse or dedicated mode), resource allocation (in cellular and dedicated mode), and power control (in reuse mode) within a single framework. The framework prioritizes D2D dedicated mode if the D2D pair is close to each other and orthogonal resources are available. Otherwise, it allows D2D reuse mode if the D2D satisfies both the maximum distance and an additional interference criteria. For reuse mode, we present a geometric vertex search approach to solve the power allocation problem. We analytically prove the validity of this approach and show that it achieves near optimal performance. For cellular and dedicated modes, we show that frequency sharing maximizes sum rate and solve the resource allocation problem in a closed form. Our simulations demonstrate the advantages of the proposed framework in terms of the performance gains achieved in the D2D mode.

In this paper, we study the problem of secure routing in a multihop wireless ad-hoc network in the presence of randomly distributed eavesdroppers. Specifically, the locations of the eavesdroppers are modeled as a homogeneous Poisson point process (PPP) and the source-destination pair is assisted by intermediate relays using the decode-and-forward (DF) strategy. We analytically characterize the physical layer security performance of any chosen multihop path using the end-to-end secure connection probability (SCP) for both colluding and noncolluding eavesdroppers. To facilitate finding an efficient solution to secure routing, we derive accurate approximations of the SCP. Based on the SCP approximations, we study the secure routing problem, which is defined as finding the multihop path having the highest SCP. A revised Bellman–Ford algorithm is adopted to find the optimal path in a distributed manner. Simulation results demonstrate that the proposed secure routing scheme achieves nearly the same performance as exhaustive search.

In this paper, we study physical layer security in an underlay cognitive radio (CR) network. We consider the problem of secure communication between a secondary transmitter-receiver pair in the presence of randomly distributed eavesdroppers under an interference constraint set by the primary user. For different channel knowledge assumptions at the transmitter, we design four transmission protocols to achieve the secure transmission in the CR network. We give a comprehensive performance analysis for each protocol in terms of transmission delay, security, reliability, and the overall secrecy throughput. Furthermore, we determine the optimal design parameter for each transmission protocol by solving the optimization problem of maximizing the secrecy throughput subject to both security and reliability constraints. Numerical results illustrate the performance comparison between different transmission protocols.

Theoretical studies on physical layer security often adopt the secrecy outage probability as the performance metric for wireless communications over quasi-static fading channels. The secrecy outage probability has two limitations from a practical point of view: 1) it does not give any insight into the eavesdropper's decodability of confidential messages and 2) it cannot characterize the amount of information leakage to the eavesdropper when an outage occurs. Motivated by the limitations of the secrecy outage probability, we propose three new secrecy metrics for secure transmissions over quasi-static fading channels. The first metric establishes a link between the concept of secrecy outage and the decodability of messages at the eavesdropper. The second metric provides an error-probability-based secrecy metric which is typically used for the practical implementation of secure wireless systems. The third metric characterizes how much or how fast the confidential information is leaked to the eavesdropper. We show that the proposed secrecy metrics collectively give a more comprehensive understanding of physical layer security over fading channels and enable one to appropriately design secure communication systems with different views on how secrecy is measured.

Energy harvesting (EH) provides a means of greatly enhancing the lifetime of wireless sensor nodes. However, the randomness inherent in the EH process may cause significant delay for performing sensing operations and transmitting sensed information to the sink. Unlike most existing studies on the delay performance of EH sensor networks, where only the energy consumption of transmission is considered, we consider the energy costs of both sensing and transmission. Specifically, we consider an EH sensor that monitors some status property and adopts a harvest-then-use protocol to perform sensing and transmission. To comprehensively study the delay performance, we consider two complementary metrics and analytically derive their statistics: 1) update age-measuring the time taken from when information is obtained by the sensor to when the sensed information is successfully transmitted to the sink, i.e., how timely the updated information at the sink is, and 2) update cycle-measuring the time duration between two consecutive successful transmissions, i.e., how frequently the information at the sink is updated. Our results show that the consideration of sensing energy cost leads to an important tradeoff between the two metrics: more frequent updates result in less timely information available at the sink.

In this paper, we propose using a wireless-powered friendly jammer to enable secure communication between a source node and destination node, in the presence of an eavesdropper. We consider a two-phase communication protocol with fixed-rate transmission. In the first phase, wireless power transfer is conducted from the source to the jammer. In the second phase, the source transmits the information-bearing signal under the protection of a jamming signal sent by the jammer using the harvested energy in the first phase. We analytically characterize the long-term behavior of the proposed protocol and derive a closed-form expression for the throughput. We further optimize the rate parameters for maximizing the throughput subject to a secrecy outage probability constraint. Our analytical results show that the throughput performance differs significantly between the single-antenna jammer case and the multiantenna jammer case. For instance, as the source transmit power increases, the throughput quickly reaches an upper bound with single-antenna jammer, while the throughput grows unbounded with multiantenna jammer. Our numerical results also validate the derived analytical results.

This paper, for the first time, examines the impact of transmitter-side correlation on the artificial-noise (AN)-aided secure transmission, based on which a new power allocation strategy for AN is devised for physical layer security enhancement. Specifically, we design a correlation-based power allocation (CPA) for AN, of which the optimality in terms of achieving the minimum secrecy outage probability is analytically proved in the large system regime with the number of transmit antennas approaching infinity. In order to fully reveal the benefits of the CPA, we derive easy-to-evaluate expressions for the secrecy outage probability achieved by the CPA. Our study demonstrates that the CPA is nearly optimal and significantly outperforms the widely used uniform power allocation (UPA) even for a moderately small number of correlated transmit antennas. Furthermore, our numerical results reveal a fundamental difference between the CPA and UPA. That is when the number of correlated transmit antennas increases, the secrecy outage probability of the CPA always reduces while the secrecy outage probability of the UPA suffers from a saturation point.

Realistic modeling of energy consumption is crucial for accurate performance analysis of wireless-powered sensor nodes. In this paper, we analyze the performance of wireless-powered sensor transmissions taking into account both the energy cost of sensing and transmission. We consider a sensor that is harvesting energy from an ambient radio-frequency (RF) signal and using this energy to perform sensing and transmission. Since energy harvesting is time-varying in nature, it introduces a delay in the sensor transmissions. We study two delay-related metrics, one measuring how frequent the sensed information is updated at the sink and the other measuring the time taken from the sensing operation to successful transmission of sensed information. We analytically characterize the statistical behavior of both metrics and find an important tradeoff between them. In particular, our results illustrate that more frequent update of sensed information at the sink increases the time taken from the sensing operation to successful transmission of sensed information.

In this paper, we consider a cooperative underlay cognitive radio network in which the primary network (PN) consists of a transmitter and receiver and the secondary network (SN) has K bidirectional half-duplex relays. In the SN, two secondary transceivers adopt multiple access broadcast protocol for the secondary data transmission and at each bidirectional relay, there exist two buffers of size L data elements. Hence, each relay can store the incoming secondary data and retransmit it in an appropriate time slot later. We propose a novel buffer-aided bidirectional relay selection policy with secondary power minimization and successive interference cancellation in which the interference between the PN and SN is eliminated. Since buffers are used at the relays, data transmission in the SN is not limited to a predefined schedule. Hence, at each time slot, based on the instantaneous buffer state information of the relays and the instantaneous or statistical channel state information of the involved links, the SN makes a decision. The SN decides optimally when to use one of the relays for the multiple access, use one of the relays for the broadcast mode or be silent provided that the data transmission in both the PN and SN are error free and the secondary power expenditure is minimized. Simulation results show that the proposed scheme minimizes the secondary power expenditure, and achieves up to 40% improvement in the secondary throughput for 6 middle relays compared to the other recently proposed policies without buffer.

We design a linear precoder based on the principles of the generalized regularized channel inversion (RCI) precoder that achieves confidential broadcasting in a two-cell network. In each cell of the network, an N-antenna base station (BS) communicates with K single-antenna users. We consider coordinated beamforming where the BSs in the two cells do not share messages but the users in the two cells feed back their channel state information to both BSs. In the precoder design, we determine the optimal regularization parameter that maximizes the secrecy sum rate. To this end, we derive new channel-independent expressions for the secrecy sum rate in the large-system regime, where K and N approach infinity with a fixed ratio μ = K/N. Moreover, we propose a power-reduction strategy that significantly improves the secrecy sum rate at high transmit signal-to-noise ratios when μ is higher than 0.5.

This paper considers a heterogeneous multicell network where the base station (BS) in each cell communicates with its cell-edge user with the assistance of an amplify-and-forward relay node. Equipped with a power splitter and a wireless energy harvester, the relay scavenges RF energy from the received signals to process and forward the information. In the face of strong intercell interference and limited radio resources, we develop a resource allocation scheme that jointly optimizes (i) BS transmit powers, (ii) power splitting factors for energy harvesting and information processing at the relays, and (iii) relay transmit powers. To solve the highly non-convex problem formulation of sum-rate maximization, we propose to apply the successive convex approximation (SCA) approach and devise an iterative algorithm based on geometric programming. The proposed algorithm transforms the nonconvex problem into a sequence of convex problems, each of which is solved very efficiently by the interior-point method. We prove that our developed algorithm converges to an optimal solution that satisfies the Karush-Kuhn-Tucker conditions of the original nonconvex problem. Numerical results confirm that our joint optimization solution substantially improves the network performance, compared to the existing solution wherein only the received power splitting factors at the relays are optimized.

We consider wireless-powered amplify-and-forward relaying in cooperative communications and propose block-wise time-switching based energy harvesting protocol to implement wireless energy harvesting (EH) and information transmission (IT) at the energy constrained relay node. The time-switching EH protocol switches the relay operation between EH and IT such that during EH, relay harvests energy through the received radio-frequency signal from the source and during IT, the relay receives information signal from the source and uses the harvested energy to amplify and forward source signal to the destination. In our proposed block-wise time-switching EH protocol, the whole transmission block time is used for either EH or IT. The attractive feature of our proposed protocol is that the relay transmits at preset fixed transmit power and no channel state information is required either by the source or relay node. We derive exact expression of the analytical throughput for the proposed protocol and verify it through simulation. In addition, we show that our proposed protocol outperforms the existing time-switching EH protocol because it allows efficient use of resources by intelligently switching between EH and IT in an online fashion.

This paper analyzes the performance of the primary users (PUs) and secondary users (SUs) in an arbitrarily-shaped underlay cognitive network. In order to meet the interference threshold requirement for a primary receiver at an arbitrary location, we consider different SU activity protocols that limit the number of active SUs. We propose a framework, based on the moment-generating function of the interference due to a random SU, to analytically compute the outage probability in the primary network, as well as the average number of active SUs in the secondary network. We also propose a cooperation-based SU activity protocol in the underlay cognitive network that includes the existing threshold-based protocol as a special case. We study the average number of active SUs for the different SU activity protocols, subject to a given outage probability constraint at the PU, and we employ it as an analytical approach to compare the effect of different SU activity protocols on the performance of the primary and secondary networks.

We consider wireless-powered amplify-and-forward and decode-and-forward relaying in cooperative communications, where an energy constrained relay node first harvests energy through the received radio-frequency signal from the source and then uses the harvested energy to forward the source information to the destination node. We propose time-switching based energy harvesting (EH) and information transmission (IT) protocols with two modes of EH at the relay. For continuous time EH, the EH time can be any percentage of the total transmission block time. For discrete time EH, the whole transmission block is either used for EH or IT. The proposed protocols are attractive because they do not require channel state information at the transmitter side and enable relay transmission with preset fixed transmission power. We derive analytical expressions of the achievable throughput for the proposed protocols. The derived expressions are verified by comparison with simulations and allow the system performance to be determined as a function of the system parameters. Finally, we show that the proposed protocols outperform the existing fixed time duration EH protocols in the literature, since they intelligently track the level of the harvested energy to switch between EH and IT in an online fashion, allowing efficient use of resources.

In a mobile ad hoc network (MANET), effective prediction of time-varying interferences can enable adaptive transmission designs and therefore improve the communication performance. This paper investigates interference prediction in MANETs with a finite number of nodes by proposing and using a general-order linear model for node mobility. The proposed mobility model can well approximate node dynamics of practical MANETs. In contrast to previous studies on interference statistics, we are able through this model to give a best estimate of the time-varying interference at any time rather than long-term average effects. Specifically, we propose a compound Gaussian point process functional as a general framework to obtain analytical results on the mean value and moment-generating function of the interference prediction. With a series form of this functional, we give the necessary and sufficient condition for when the prediction is essentially equivalent to that from a binomial point process (BPP) network in the limit as time goes to infinity. These conditions permit one to rigorously determine when the commonly used BPP approximations are valid. Finally, our simulation results corroborate the effectiveness and accuracy of the analytical results on interference prediction and also show the advantages of our method in dealing with complex mobilities.

We design linear precoders that perform confidential broadcasting in multi-cell networks for two different forms of base station (BS) cooperation, namely, multi-cell processing (MCP) and coordinated beamforming (CBf). We consider a two-cell network where each cell consists of an $N$-antenna BS and $K$ single-antenna users. For such a network, we design a linear precoder based on the regularized channel inversion (RCI) for the MCP and a linear precoder based on the generalized RCI for the CBf. For each form of BS cooperation, we derive new channel-independent expressions to approximate the secrecy sum rate achieved by the precoder in the large system regime where $K,N\rightarrow\infty$ with a fixed ratio $\beta=K/N$. Using these results, we determine the optimal regularization parameters of the RCI and the generalized RCI precoders that maximize the secrecy sum rate for the MCP and the CBf, respectively. We further propose power-reduction strategies that significantly increase the secrecy sum rate at high transmit signal-to-noise ratios when the network load is high. Our numerical results substantiate the derived expressions, verify the optimality of the determined optimal regularization parameters, and demonstrate the performance improvement offered by the proposed power-reduction strategies.

The existing research on physical layer security commonly assumes the number of eavesdropper antennas to be known. Although this assumption allows one to easily compute the achievable secrecy rate, it can hardly be realized in practice. In this paper, we provide an innovative approach to studying secure communication systems without knowing the number of eavesdropper antennas by introducing the concept of spatial constraint into physical layer security. Specifically, the eavesdropper is assumed to have a limited spatial region to place (possibly an infinite number of) antennas. From a practical point of view, knowing the spatial constraint of the eavesdropper is much easier than knowing the number of eavesdropper antennas. We derive the achievable secrecy rates of the spatially-constrained system with and without friendly jamming. We show that a non-zero secrecy rate is achievable with the help of a friendly jammer, even if the eavesdropper places an infinite number of antennas in its spatial region. Furthermore, we find that the achievable secrecy rate does not monotonically increase with the jamming power, and hence, we obtain the closed-form solution of the optimal jamming power that maximizes the secrecy rate.

We present an optimized secure multi-antenna transmission approach based on artificial-noise-aided beamforming, with limited feedback from a desired single-antenna receiver. To deal with beamformer quantization errors as well as unknown eavesdropper channel characteristics, our approach is aimed at maximizing throughput under dual performance constraints-a connection outage constraint on the desired communication channel and a secrecy outage constraint to guard against eavesdropping. We propose an adaptive transmission strategy that judiciously selects the wiretap coding parameters, as well as the power allocation between the artificial noise and the information signal. This optimized solution reveals several important differences with respect to solutions designed previously under the assumption of perfect feedback. We also investigate the problem of how to most efficiently utilize the feedback bits. The simulation results indicate that a good design strategy is to use approximately 20% of these bits to quantize the channel gain information, with the remainder to quantize the channel direction, and this allocation is largely insensitive to the secrecy outage constraint imposed. In addition, we find that 8 feedback bits per transmit antenna is sufficient to achieve approximately 90% of the throughput attainable with perfect feedback.

This paper characterizes the aggregate interference at the primary user (PU) due to M secondary users (SUs) in an underlay cognitive network, where appropriate SU activity protocols are employed in order to limit the interference generated by the SUs. Different from prior works, we assume that the PU can be located anywhere inside an arbitrarily-shaped convex network region. Using the moment generating function (MGF) of the interference from a random SU, we derive general expressions for the n-th moment and the n-th cumulant of the aggregate interference for guard zone and multiple-threshold SU activity protocols. Using the cumulants, we study the convergence of the distribution of the aggregate interference to a Gaussian distribution. In addition, we compare the well-known closed-form distributions in the literature to approximate the complementary cumulative distribution function (CCDF) of the aggregate interference. Our results show that care must be undertaken in approximating the aggregate interference as a Gaussian distribution, even for a large number of SUs, since the convergence is not monotonie in general. In addition, the shifted lognormal distribution provides the overall best CCDF approximation, especially in the distribution tail region, for arbitrarily-shaped network regions.

For secure communications over wireless fading channels, the secrecy outage probability is widely used as the performance measure. However, the current secrecy outage formulation has two major limitations in evaluating the secrecy performance: a) the amount of information leakage to the eavesdropper cannot be characterized when an outage occurs, b) the current formulation does not give insights into the eavesdropper's decodability of confidential messages. To overcome such limitations and obtain in-depth understanding of secrecy performance over wireless fading channels, this paper proposes three new secrecy measures for different practical aims, namely, 1) generalized secrecy outage probability, 2) asymptotic lower bound on eavesdropper's decoding error probability, and 3) average information leakage rate. A specific example of wireless transmissions with a fixed-rate wiretap code is given to illustrate the use of the proposed secrecy measures.

We study secure multi-antenna transmission with limited feedback from the intended receiver and no feedback from the malicious eavesdropper. Our system uses the artificial-noise-aided beamforming approach to enhance secrecy, considering slow fading channels with outage constraints on the reliability performance of legitimate communication and the secrecy performance against eavesdropping. Our analytical results provide conditions on the minimum number of feedback bits and the minimum strength of the intended channel for making secure transmission possible. We observe that strengthening the secrecy outage constraint puts higher requirements on the number of feedback bits and the strength of the intended channel. To maximize the achievable secrecy rate, the optimal transmit power allocation between the information signal and the artificial noise is also derived in closed form.

In this paper, we consider a decode-and-forward (DF) relaying network based on wireless energy harvesting. The energy constrained relay node first harvests energy through radio-frequency (RF) signals from the source node. Next, the relay node uses the harvested energy to forward the decoded source information to the destination node. The source node transfers energy and information to the relay node through two mechanisms, i) time switching-based relaying (TSR) and ii) power splitting-based relaying (PSR). Considering wireless energy harvesting constraint at the relay node, we derive the exact analytical expressions of the achievable throughput and ergodic capacity of a DF relaying network for both TSR and PSR schemes. Through numerical analysis, we study the throughput performance of the overall system for different system parameters, such as energy harvesting time, power splitting ratio, and signal-to-noise-ratio (SNR). In particular, the throughput performance of the PSR scheme outperforms the throughput performance of the TSR scheme for a wide range of SNRs.

This paper studies the discriminatory channel estimation (DCE) performance between a legitimate receiver (LR) and an unauthorized receiver (UR) in the multiple-input multiple-output (MIMO) wireless systems. DCE is a recently developed concept that intentionally degrades the channel estimation at the UR so as to minimize the probability of confidential information being eavesdropped by the UR. Usually, the existing DCE scheme is based on the linear minimum mean square error (LMMSE) method with two-way training. In this paper, we propose a new two-way training for DCE based on semiblind approach, e.g., the whitening-rotation (WR)-based channel estimator. To characterize the DCE performance, we derive the closed-form of the normalized mean squared error (NMSE) to the channel estimation at both the LR and the UR. Simulation results show that the proposed two-way training achieves higher performance compared to the two-way training designs in the literature.

In this paper, we consider a wireless-powered cooperative communication network, which consists of a hybrid access-point (AP), a hybrid relay, and an information source. In contrast to the conventional cooperative networks, the source in the considered network is assumed to have no embedded energy supply. Thus, it first needs to harvest energy from the signals broadcast by the AP and/or relay, which have constant power supply, in the downlink (DL) before transmitting the information to the AP in the uplink (UL). The hybrid relay can not only help to forward information in the UL but also charge the source with wireless energy transfer in the DL. Considering different possible operations of the hybrid relay, we propose two cooperative protocols for the considered network. We jointly optimize the time and power allocation for DL energy transfer and UL information transmission to maximize the system throughput of the proposed protocols. Numerical results are presented to compare the performance of the proposed protocols and illustrate the impacts of system parameters.

This paper analyzes the outage performance in finite wireless networks. Unlike most prior works, which either assumed a specific network shape or considered a special location of the reference receiver, we propose two general frameworks for analytically computing the outage probability at any arbitrary location of an arbitrarily-shaped finite wireless network: (i) a moment generating function-based framework which is based on the numerical inversion of the Laplace transform of a cumulative distribution and (ii) a reference link power gain-based framework which exploits the distribution of the fading power gain between the reference transmitter and receiver. The outage probability is spatially averaged over both the fading distribution and the possible locations of the interferers. The boundary effects are accurately accounted for using the probability distribution function of the distance of a random node from the reference receiver. For the case of the node locations modeled by a Binomial point process and Nakagami-m fading channel, we demonstrate the use of the proposed frameworks to evaluate the outage probability at any location inside either a disk or polygon region. The analysis illustrates the location-dependent performance in finite wireless networks and highlights the importance of accurately modeling the boundary effects.

Discriminatory channel estimation (DCE) is a recently developed strategy to enlarge the performance difference between a legitimate receiver (LR) and an unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless system. Specifically, it makes use of properly designed training signals to degrade channel estimation at the UR, which in turn limits the UR's eavesdropping capability during data transmission. In this paper, we propose a new two-way training scheme for DCE through exploiting a whitening-rotation (WR) based semiblind method. To characterize the performance of DCE, a closed-form expression of the normalized mean squared error (NMSE) of the channel estimation is derived for both the LR and the UR. Furthermore, the developed analytical results on NMSE are utilized to perform optimal power allocation between the training signal and artificial noise (AN). The advantages of our proposed DCE scheme are twofold: Compared with the existing DCE scheme based on the linear minimum mean square error (LMMSE) channel estimator, the proposed scheme adopts a semiblind approach and achieves better DCE performance; and the proposed scheme is robust against active eavesdropping with the pilot contamination attack, whereas the existing scheme fails under such an attack.

Relay transmission can enhance coverage and throughput, whereas it can be vulnerable to eavesdropping attacks due to the additional transmission of the source message at the relay. Thus, whether or not one should use relay transmission for secure communication is an interesting and important problem. In this paper, we consider the transmission of a confidential message from a source to a destination in a decentralized wireless network in the presence of randomly distributed eavesdroppers. The source-destination pair can be potentially assisted by randomly distributed relays. For an arbitrary relay, we derive exact expressions of secure connection probability for both colluding and noncolluding eavesdroppers. We further obtain lower bound expressions on the secure connection probability, which are accurate when the eavesdropper density is small. Using these lower bound expressions, we propose a relay selection strategy to improve the secure connection probability. By analytically comparing the secure connection probability for direct transmission and relay transmission, we address the important problem of whether or not to relay and discuss the condition for relay transmission in terms of the relay density and source-destination distance. These analytical results are accurate in the small eavesdropper density regime.

Backscatter wireless communication lies at the heart of many practical low-cost, low-power, distributed passive sensing systems. The inherent cost restrictions coupled with the modest computational and storage capabilities of passive sensors, such as RFID tags, render the adoption of classical security techniques challenging; which motivates the introduction of physical layer security approaches. Despite their promising potential, little has been done to study the prospective benefits of such physical layer techniques in backscatter systems. In this paper, the physical layer security of wireless backscatter systems is studied and analyzed. First, the secrecy rate of a basic single-reader, single-tag model is studied. Then, the unique features of the backscatter channel are exploited to maximize this secrecy rate. In particular, the proposed approach allows a backscatter system's reader to inject a noise-like signal, added to the conventional continuous wave signal, in order to interfere with an eavesdropper's reception of the tag's information signal. The benefits of this approach are studied for a variety of scenarios while assessing the impact of key factors, such as antenna gains and location of the eavesdropper, on the overall secrecy of the backscatter transmission. Numerical results corroborate our analytical insights and show that, if properly deployed, the injection of artificial noise yields significant performance gains in terms of improving the secrecy of backscatter wireless transmission.

Small cell network (SCN) offers, for the first time, a low-cost and scalable mechanism to meet the forecast data-traffic demand. In this paper, we propose a non-uniform SCN deployment scheme. The small cell base stations (BSs) in this scheme will not be utilized in the region within a prescribed distance away from any macrocell BSs, defined as the inner region. Based upon the analytical framework provided in this work, the downlink coverage and single user throughput are precisely characterized. Provided that the inner region size is appropriately chosen, we find that the proposed non-uniform SCN deployment scheme can maintain the same level of cellular coverage performance even with 50% less small cell BSs used than the uniform SCN deployment, which is commonly considered in the literature. Furthermore, both the coverage and the single user throughput performance will significantly benefit from the proposed scheme, if its average small cell density is kept identical to the uniform SCN deployment. This work demonstrates the benefits obtained from a simple non-uniform SCN deployment, thus highlighting the importance of deploying small cells selectively.

This paper proposes a coverage-oriented femtocell network deployment scheme, in which the femtocell base stations (BSs) can decide whether to be active or inactive depending on their distances from the macrocell BSs. Specifically, as the areas close to the macrocell BSs already have satisfactory cellular coverage, the femtocell BSs located inside such areas are kept to be inactive. Thus, all the active femtocells are located in the poor macrocell coverage areas. Based on a stochastic geometric framework, the coverage probability can be analyzed with tractable results. Surprisingly, the results show that the proposed scheme, although with a lower defacto femtocell density, can achieve better coverage performance than that keeping all femtocells in the entire network to be active. The analytical results further identify the achievable optimal performance of the new scheme, which provides mobile operators a guideline for femtocell deployment and operation.

This paper studies the information-theoretic secrecy performance in large-scale cellular networks based on a stochastic geometry framework. The locations of both base stations and the mobile users are modeled as independent two-dimensional Poisson point processes. We consider a key feature of the cellular network, namely, information exchange between base stations, and characterize its impact on the achievable secrecy rate of an arbitrary downlink transmission with a certain portion of the mobile users acting as potential eavesdroppers. In particular, analytical results are presented under diverse assumptions on the availability of eavesdroppers' location information at the serving base station, which captures the benefit from the exchange of mobile users' location information between base stations.

Multirelay networks exploit spatial diversity by transmitting user's messages through multiple relay paths. Most works in the literature on cooperative or relay networks assume that all terminals are fully cooperative and neglect the effect of possibly existing malicious relay behaviors. In this work, we consider a multirelay network that consists of both cooperative and malicious relays, and aims to obtain an improved understanding on the optimal behaviors of these two groups of relays via information-theoretic mutual information games. By modeling the set of cooperative relays and the set of malicious relays as two players in a zero-sum game with the maximum achievable rate as the utility, the optimal transmission strategies of both types of relays are derived by identifying the Nash equilibrium of the proposed game. Our main contributions are twofold. First, a generalization to previous works is obtained by allowing malicious relays to either listen or attack in Phase 1 (source-relay transmission phase). This is in contrast to previous works that only allow the malicious relays to listen in Phase 1 and to attack in Phase 2 (relay-destination transmission phase). The latter is shown to be suboptimal in our problem. Second, the impact of CSI knowledge at the destination on the optimal attack strategy that can be adopted by the malicious relays is identified. In particular, for the more practical scenario where the interrelay CSI is unknown at the destination, the constant attack is shown to be optimal as opposed to the commonly considered Gaussian attack.

Physical layer security has recently been regarded as an emerging technique to complement and improve the communication security in future wireless networks. The current research and development in physical layer security are often based on the ideal assumption of perfect channel knowledge or the capability of variable-rate transmissions. In this paper, we study the secure transmission design in more practical scenarios by considering channel estimation errors at the receiver and investigating both fixed-rate and variable-rate transmissions. Assuming quasi-static fading channels, we design secure on-off transmission schemes to maximize the throughput subject to a constraint on secrecy outage probability. For systems with given and fixed encoding rates, we show how the optimal on-off transmission thresholds and the achievable throughput vary with the amount of knowledge on the eavesdropper's channel. In particular, our design covers the interesting case where the eavesdropper also uses the pilots sent from the transmitter to obtain imperfect channel estimation. An interesting observation is that using too much pilot power can harm the throughput of secure transmission if both the legitimate receiver and the eavesdropper have channel estimation errors, while the secure transmission always benefits from increasing pilot power when only the legitimate receiver has channel estimation errors but not the eavesdropper. When the encoding rates are controllable parameters to design, we further derive both a non-adaptive and an adaptive rate transmission schemes by jointly optimizing the encoding rates and the on-off transmission thresholds to maximize the throughput of secure transmissions.

We study physical-layer security in wireless ad hoc networks and investigate two types of multi-antenna transmission schemes for providing secrecy enhancements. To establish secure transmission against malicious eavesdroppers, we consider the generation of artificial noise with either sectoring or beamforming. For both approaches, we provide a statistical characterization and tradeoff analysis of the outage performance of the legitimate communication and the eavesdropping links. We then investigate the network-wide secrecy throughput performance of both schemes in terms of the secrecy transmission capacity, and study the optimal power allocation between the information signal and the artificial noise. Our analysis indicates that, under transmit power optimization, the beamforming scheme outperforms the sectoring scheme, except for the case where the number of transmit antennas are sufficiently large. Our study also reveals some interesting differences between the optimal power allocation for the sectoring and beamforming schemes.

An emerging solution for prolonging the lifetime of energy constrained relay nodes in wireless networks is to avail the ambient radio-frequency (RF) signal and to simultaneously harvest energy and process information. In this paper, an amplify-and-forward (AF) relaying network is considered, where an energy constrained relay node harvests energy from the received RF signal and uses that harvested energy to forward the source information to the destination. Based on the time switching and power splitting receiver architectures, two relaying protocols, namely, i) time switching-based relaying (TSR) protocol and ii) power splitting-based relaying (PSR) protocol are proposed to enable energy harvesting and information processing at the relay. In order to determine the throughput, analytical expressions for the outage probability and the ergodic capacity are derived for delay-limited and delay-tolerant transmission modes, respectively. The numerical analysis provides practical insights into the effect of various system parameters, such as energy harvesting time, power splitting ratio, source transmission rate, source to relay distance, noise power, and energy harvesting efficiency, on the performance of wireless energy harvesting and information processing using AF relay nodes. In particular, the TSR protocol outperforms the PSR protocol in terms of throughput at relatively low signal-to-noise-ratios and high transmission rates.

This paper studies the information-theoretic secrecy performance in large-scale cellular networks based on a stochastic geometry framework. The locations of both base stations and mobile users are modeled as independent two-dimensional Poisson point processes. We consider two important features of cellular networks, namely, information exchange between base stations and cell association, to characterize their impact on the achievable secrecy rate of an arbitrary downlink transmission with a certain portion of the mobile users acting as potential eavesdroppers. In particular, tractable results are presented under diverse assumptions on the availability of eavesdroppers' location information at the serving base station, which captures the benefit from the exchange of the location information between base stations.

In this paper, we analyze the performance of cooperative transmissions in wireless ad hoc networks with random node locations. According to a contention probability for message transmission, each source node can either transmits its own message signal or acts as a potential relay for others. Hence, each destination node can potentially receive two copies of the message signal, one from the direct link and the other from the relay link. Taking the random node locations and interference into account, we derive closed-form expressions for the outage probability with different combining schemes at the destination nodes. In particular, the outage performance of optimal combining, maximum ratio combining, and selection combining strategies are studied and quantified.

Cooperative jamming as a physical layer security enhancement has recently drawn considerable attention. While most existing works focus on communication systems with a small number of nodes, we investigate the use of cooperative jamming for providing secrecy in large-scale decentralized networks consisting of randomly distributed legitimate users and eavesdroppers. A modified slotted ALOHA protocol, named CJ-ALOHA, is considered where each legitimate transmitter either sends its message signal or acts as a helping jammer according to a message transmission probability p. We derive the secrecy transmission capacity to characterize the network throughput and show how the throughput is affected by the CJ-ALOHA protocol. Both analytical and numerical insights are provided on the design of the CJ-ALOHA protocol for optimal throughput performance.

Physical layer security has emerged as a promising technique that complements existing cryptographic approaches and enables the securing of wireless transmissions against eavesdropping. In this paper, the impact of optimizing physical layer security metrics on the architecture and interactions of the nodes in multi-hop wireless networks is studied. In particular, a game-theoretic framework is proposed using which a number of nodes interact and choose their optimal and secure communication paths in the uplink of a wireless multi-hop network, in the presence of eavesdroppers. To this end, a tree formation game is formulated in which the players are the wireless nodes that seek to form a network graph among themselves while optimizing their multi-hop secrecy rates or the path qualification probabilities, depending on their knowledge of the eavesdroppers' channels. To solve this game, a distributed tree formation algorithm is proposed and is shown to converge to a stable Nash network. Simulation results show that the proposed approach yields significant performance gains in terms of both the average bottleneck secrecy rate per node and the average path qualification probability per node, relative to classical best-channel algorithms and the single-hop star network. The results also assess the properties and characteristics of the resulting Nash networks.

Existing studies on physical layer security often assume the availability of perfect channel state information (CSI) and overlook the importance of channel training needed for obtaining the CSI. In this letter, we discuss how an active eavesdropper can attack the training phase in wireless communication to improve its eavesdropping performance. We derive a new security attack from the pilot contamination phenomenon, which targets at systems using reverse training to obtain the CSI at the transmitter for precoder design. This attack changes the precoder used by the legitimate transmitter in a controlled manner to strengthen the signal reception at the eavesdropper during data transmission. Furthermore, we discuss an efficient use of the transmission energy of an advanced full-duplex eavesdropper to simultaneously achieve a satisfactory eavesdropping performance whilst degrading the detection performance of the legitimate receiver.

This paper examines the use of two-way training in multiple-input multiple-output (MIMO) wireless systems to discriminate the channel estimation (and, thus, data detection) performance between two receivers, namely, a legitimate receiver (LR) and an unauthorized receiver (UR). This work extends upon the discriminatory channel estimation (DCE) proposed in our prior work, where it was previously assumed that training signals can only be sent by the transmitter. The DCE design criterion is to minimize the channel estimation error at the LR while confining the channel estimation error at the UR above a minimum level. In the case of two-way training, training signals can first be transmitted on the reverse link to enable channel estimation at the transmitter and allow the transmitter to insert artificial noise (AN) along with the training signal in the forward link to disrupt the training at the UR, while minimizing the interference on the LR. The optimal power allocation between training and AN signals is devised for systems that are subject to both average and peak power constraints. Numerical results demonstrate the efficacy of the proposed two-way training scheme when used in discriminating the performances between LR and UR.

This paper studies training-based transmissions over multiple-input multiple-output (MIMO) fading channels in the presence of jamming. Each transmission block consists of a training phase and a data transmission phase. From an information-theoretic viewpoint, we formulate a max-min problem on the energy allocation between the two phases. The legitimate user of the channel aims to design a robust energy allocation strategy which maximizes its data rate under the worst case scenario assuming that the jammer is able to optimize its jamming energy allocation between the training phase and the data transmission phase. For a fixed training length, we derive an analytical solution to the robust energy allocation. When the training length is allowed to vary, we show that a robust design of the training length is generally larger than the number of transmit antennas and approaches half of the block length at low signal to jamming and noise ratio (SJNR). Our numerical results demonstrate a potential of 20%-40% performance gain by using the proposed robust designs in various scenarios.

We formulate a capacity lower bound for the dual-hop wireless relay channel which employs an amplify-and-forward (AF) protocol at the relay node. In AF relaying, even when the fading channel in both hops is complex Gaussian distributed, the overall dual-hop channel is non-Gaussian. WPe highlight that there is a fundamental difference between Gaussian and non-Gaussian channels in terms of deriving their capacity lower bound. Specifically for non-Gaussian channels, the channel estimation error variance depends on the received pilot signal and is, in general, different from the average error variance. Whereas for Gaussian distributed channels, which have been predominantly studied in the literature, the channel estimation error variance conditioned on the observed pilot signal coincides with the average error variance. We provide an example using the AF dual-hop channel to exhibit the numerical difference between the true capacity lower bound and that obtained by using the average instead of the conditional error variance.

This paper investigates the problem of spectrally efficient operation of a multiuser uplink cognitive radio system in the presence of a single primary link. The secondary system applies opportunistic interference cancelation (OIC) and decodes the primary signal when such an opportunity is created. We derive the achievable rate in the secondary system when OIC is used. This scheme has a practical significance, since it enables rate adaptation without requiring any action from the primary system. The exact expressions for outage probability of the primary user are derived, when the primary system is exposed to interference from secondary users. Moreover, approximated formulas and tight lower and upper bounds for the ergodic sum-rate capacity of the secondary network are found. Next, the power allocation is investigated in the secondary system for maximizing the sum-rate under an outage constraint at the primary system. We formulate the power optimization problem in various scenarios depending on the availability of channel state information and the type of power constraints, and propose a set of simple solutions. Finally, the analytical results are confirmed by simulations, indicating both the accuracy of the analysis, and the fact that the spectral-efficient, low-complexity, flexible, and high-performing cognitive radio can be designed based on the proposed schemes.

Information-theoretic security constraints reduce the connectivity of wireless networks in the presence of eavesdroppers, which motivates better modeling of such networks and the development of techniques that are robust to eavesdropping. In this letter, we are concerned with the existence of secure connections from a typical transmitter to the legitimate receiver(s) over fading channels, where the legitimate nodes and eavesdroppers are all randomly located. We consider non-colluding and colluding eavesdroppers, and derive the network secure connectivity for both eavesdropper strategies. We mathematically show how nodes with multiple transmit antenna elements can improve secure connectivity by forming a directional antenna or using eigen-beamforming. Compared with single antenna transmission, a large connectivity improvement can be achieved by both multi-antenna transmission techniques even with a small number of antennas.

This paper studies the throughput of large-scale decentralized wireless networks with physical layer security constraints. In particular, we are interested in the question of how much throughput needs to be sacrificed for achieving a certain level of security. We consider random networks where the legitimate nodes and the eavesdroppers are distributed according to independent two-dimensional Poisson point processes. The transmission capacity framework is used to characterize the area spectral efficiency of secure transmissions with constraints on both the quality of service (QoS) and the level of security. This framework illustrates the dependence of the network throughput on key system parameters, such as the densities of legitimate nodes and eavesdroppers, as well as the QoS and security constraints. One important finding is that the throughput cost of achieving a moderate level of security is quite low, while throughput must be significantly sacrificed to realize a highly secure network. We also study the use of a secrecy guard zone, which is shown to give a significant improvement on the throughput of networks with high security requirements.

Connectivity is a fundamental requirement in the planning, design and evaluation of vehicular ad hoc networks (VANET). In this paper, we propose a new equivalent speed parameter and develop an analytical model to explain the effect of vehicle mobility on the connectivity of highway segments in a VANET. We prove that the equivalent speed is different from the average vehicle speed and it decreases as the standard deviation of the vehicle speed increases. Using the equivalent speed we derive a novel analytical expression for the average number of vehicles on a highway segment, which allows us to accurately predict the network 1 connectivity. We verify the correctness of our analytical approach by comparing the numerical results with simulations. The results show that increasing the average vehicle speed increases the equivalent speed, which leads to a decrease in the average number of vehicles on a highway segment and consequently degrades connectivity. On the other hand increasing the standard deviation of the vehicle speed decreases the equivalent speed, which leads to an increase in the average number of vehicles on a highway segment and consequently improves connectivity. The results also show that vehicles in a VANET can adaptively choose their transmission range to ensure network connectivity in highway segments while minimising power consumption.

We study the design of training-based multiple-input multiple-output systems in two block-wise transmission schemes. The conventional transmission scheme has a fixed amount of energy to be used in each block, hence transmission takes place in every block. For this scheme, we study the optimality of using all available time in each block for transmission and provide bounds to significantly reduce the ranges of the possible values of the optimal training and data lengths. The second scheme, called the flashy transmission scheme, is constrained by an average amount of energy per block, and uses some but not necessarily all blocks for transmission. For this scheme, we find the optimal fraction of blocks to be used for transmission. When this optimal fraction is less than one, we show that the optimal training and data lengths are independent of the energy constraint.

In this letter, we consider multiple-input single-output (MISO) systems with two-way training based transmission. We focus on the long-term system performance and study the optimal power allocation between reverse training, forward training and data transmission. We derive closed-form solutions for the optimal power allocation using high signal-to-noise ratio (SNR) approximations, and show that they achieve near optimal performance in terms of symbol error rate (SER) for different modulation schemes over a wide range of SNR values.

In this paper, we consider multiple-input multiple-output (MIMO) communication systems with combined channel covariance feedback (CCF) and channel gain feedback (CGF), hereafter called hybrid CCF-CGF systems. Using an ergodic capacity lower bound as the figure of merit, we investigate the optimal training and data transmission strategies as well as the optimal transmit resource allocation. We prove that the optimal structure for data transmission follows a water-filling solution according to the estimated channel gains, rotated and truncated into the trained eigen-directions. We analytically find the range of the optimal training length. Through numerical evaluations we also show that a closed-form solution of the training power allocation achieves near optimal performance. Finally, we show that the capacity of hybrid CCF-CGF systems can be significantly increased by adding extra transmit antennas without increasing the training resources or feedback overhead.

We study the optimal antenna configuration (i.e. number of transmit and receive antennas) for multiple-input multiple-output systems in pilot-symbol-assisted modulation schemes with imperfect channel estimation. We assume block flat-fading channels and focus on a practical range of high signal-to-noise ratio. An ergodic capacity lower bound is used as the objective function to be maximized. We analytically study the capacity gain from adding extra antennas to the transmitter or to the receiver in two different scenarios. Our numerical results show that the optimal antenna configuration under imperfect channel estimation can be significantly different from that under perfect channel estimation assumption. In addition, we investigate the capacity gain from optimizing antenna configuration and find that the gain can be larger than that achieved by optimizing transmit power over pilot and data symbols, particularly for large block lengths.

Random beamforming, where each node selects a main beam direction without any coordination with other nodes, has been proposed as a simple technique to improve connectivity in wireless ad hoc networks. This paper presents an analytical model for evaluating the impact of random beamforming on the connectivity of wireless ad hoc networks in the presence of path loss and shadowing effects. We investigate the connectivity with random beamforming from the view points of a single node and the entire network. The correctness of our analytical approach is validated by comparing the analytical results with simulations. We show that for a path loss exponent of alpha<3, irrespective of shadowing effects, random beamforming improves both the local and overall connectivity compared to omnidirectional antennas.

We study the design parameters of pilot-symbol-assisted modulation (PSAM) schemes for spatially correlated single-input multiple-output (SIMO) systems in time-varying Gauss-Markov flat-fading channels. We use an information capacity lower bound as our figure of merit. We investigate the optimum design parameters, including the ratio of power allocated to the pilots and the fraction of time occupied by the pilots, for SIMO systems with different antenna sizes and with spatial channel correlation. Our main finding is that by optimally designing the training parameters for single-input single-output (SISO) systems, the same parameters can be used to achieve near optimum capacity in both spatially independent and correlated SIMO systems for the same fading rate and signal-to-noise ratio (SNR). In addition, we show that spatially independent channels give the lowest capacity at sufficiently low SNR. These findings provide insights into the design of practical PSAM systems.

In this paper, we develop low-complexity iterative channel estimation techniques for emerging IDMA systems. The channel estimators make use of pilots as well as soft decoded data information. We derive a lower bound for channel estimation error that reflects the reliability of soft decoded data. We show that the estimators perform close to a minimum variance unbiased estimator as the mean square error (MSE) approaches the lower bound. Numerical results on the MSE and BER performance also show that the proposed channel estimators are able to track the time-varying channel states.